“System Analysis and Design. Classification of problems according to the degree of their structuring

Send your good work in the knowledge base is simple. Use the form below

Students, graduate students, young scientists who use the knowledge base in their studies and work will be very grateful to you.

Posted on http://www.allbest.ru/

Tauride Federal University. IN AND. Vernadsky

Faculty of Mathematics and Informatics

Abstract on the topic:

"System Analysis"

Completed by a 3rd year student, 302 groups

Taganov Alexander

scientific adviser

Stonyakin Fedor Sergeevich

Plan

1. Definition of systems analysis

1.1 Model building

1.2 Statement of the research problem

1.3 Solution of the stated mathematical problem

1.4 Characteristics of the tasks of system analysis

3. System analysis procedures

4.1 Shaping the problem

4.2 Setting goals

5. Generation of alternatives

Output

Bibliography

1. System Analysis Definitions

System analysis as a discipline was formed as a result of the need to explore and design complex systems, manage them in conditions of incomplete information, limited resources and time pressure. System analysis is further development a number of disciplines, such as operations research, optimal control theory, decision theory, expert analysis, systems management theory, etc. To successfully solve the tasks set, system analysis uses the entire set of formal and informal procedures. The listed theoretical disciplines are the basis and methodological basis of system analysis. Thus, system analysis is an interdisciplinary course that generalizes the methodology for studying complex technical, natural and social systems. The widespread dissemination of ideas and methods of system analysis, and most importantly, their successful application in practice, became possible only with the introduction and widespread use of computers. It was the use of computers as a tool for solving complex problems that made it possible to move from constructing theoretical models of systems to their wide practical application. In this regard, N.N. Moiseev writes that system analysis is a set of methods based on the use of computers and focused on the study of complex systems - technical, economic, environmental, etc. The central problem of system analysis is the problem of decision making. In relation to the problems of research, design and management of complex systems, the decision-making problem is associated with the choice of a certain alternative under conditions of various kinds of uncertainty. Uncertainty is due to the multicriteria of optimization problems, the uncertainty of the goals of system development, the ambiguity of system development scenarios, the lack of a priori information about the system, the impact of random factors during the dynamic development of the system, and other conditions. Given these circumstances, systems analysis can be defined as a discipline dealing with decision-making problems in conditions where the choice of an alternative requires the analysis of complex information of various physical nature.

System analysis is a synthetic discipline. It can be divided into three main directions. These three directions correspond to three stages that are always present in the study of complex systems:

1) building a model of the object under study;

2) setting the research problem;

3) solution of the set mathematical problem. Let's consider these steps.

system mathematical generation

1.1 Model building

Building a model (formalization of the system, process or phenomenon under study) is a description of the process in the language of mathematics. When building a model, a mathematical description of the phenomena and processes occurring in the system is carried out. Since knowledge is always relative, the description in any language reflects only some aspects of the ongoing processes and is never absolutely complete. On the other hand, it should be noted that when building a model, it is necessary to focus on those aspects of the process under study that are of interest to the researcher. It is deeply erroneous to want to reflect all aspects of the system's existence when building a system model. When conducting a system analysis, as a rule, they are interested in the dynamic behavior of the system, and when describing the dynamics from the point of view of the study, there are paramount parameters and interactions, and there are parameters that are not essential in this study. Thus, the quality of the model is determined by the correspondence of the description to the requirements that apply to the study, the correspondence of the results obtained with the help of the model to the course of the observed process or phenomenon. The construction of a mathematical model is the basis of all system analysis, the central stage of research or design of any system. The result of the entire system analysis depends on the quality of the model.

1.2 Statement of the research problem

At this stage, the purpose of the analysis is formulated. The purpose of the study is assumed to be an external factor in relation to the system. Thus, the goal becomes an independent object of study. The goal must be formalized. The task of system analysis is to carry out the necessary analysis of uncertainties, limitations and, ultimately, to formulate some optimization problem.

Here X is an element of some normed space G, determined by the nature of the model, , where E - a set that can have an arbitrarily complex nature, determined by the structure of the model and the features of the system under study. Thus, the task of system analysis at this stage is treated as some kind of optimization problem. By analyzing the system requirements, i.e. the goals that the researcher intends to achieve, and the uncertainties that are inevitably present, the researcher must formulate the goal of the analysis in the language of mathematics. The optimization language turns out to be natural and convenient here, but by no means the only possible one.

1.3 Solution of the stated mathematical problem

Only this third stage of the analysis can be properly attributed to the stage that makes full use of mathematical methods. Although without knowledge of mathematics and the capabilities of its apparatus, the successful implementation of the first two stages is impossible, since formalization methods should be widely used both when building a system model and when formulating the goals and objectives of analysis. However, we note that it is at the final stage of system analysis that subtle mathematical methods may be required. But it should be borne in mind that the problems of system analysis can have a number of features that lead to the need to use heuristic approaches along with formal procedures. The reasons for turning to heuristic methods are primarily related to the lack of a priori information about the processes occurring in the analyzed system. Also, such reasons include the large dimension of the vector X and complexity of the set structure G. In this case, the difficulties arising from the need to use informal analysis procedures are often decisive. Successful solution of problems of system analysis requires the use of informal reasoning at each stage of the study. In view of this, checking the quality of the solution, its compliance with the original goal of the study turns into the most important theoretical problem.

1.4 Characteristics of the tasks of system analysis

System analysis is currently at the forefront of scientific research. It is intended to provide a scientific apparatus for the analysis and study of complex systems. The leading role of system analysis is due to the fact that the development of science has led to the formulation of the tasks that system analysis is designed to solve. The peculiarity of the current stage is that system analysis, having not yet managed to form into a full-fledged scientific discipline, is forced to exist and develop in conditions when society begins to feel the need to apply still insufficiently developed and tested methods and results and is not able to postpone decisions related to them tasks for tomorrow. This is the source of both the strength and the weakness of system analysis: strength - because it constantly feels the impact of the need for practice, is forced to continuously expand the range of objects of study and does not have the opportunity to abstract from the real needs of society; weaknesses - because often the use of "raw", insufficiently developed methods of systematic research leads to the adoption of hasty decisions, the neglect of real difficulties.

Let us consider the main tasks, to which the efforts of specialists are directed and which need further development. First, it should be noted the tasks of studying the system of interactions of the analyzed objects with the environment. The solution to this problem involves:

drawing a boundary between the system under study and the environment, which predetermines the maximum depth of influence of the considered interactions, which limits the consideration;

· definition of real resources of such interaction;

consideration of the interactions of the system under study with a higher level system.

Tasks of the following type are associated with the design of alternatives for this interaction, alternatives for the development of the system in time and space.

An important direction in the development of systems analysis methods is associated with attempts to create new possibilities for constructing original solution alternatives, unexpected strategies, unusual ideas and hidden structures. In other words, we are talking here about the development of methods and means of strengthening the inductive capabilities of human thinking, in contrast to its deductive capabilities, which, in fact, are aimed at the development of formal logical means. Research in this direction has begun only quite recently, and there is still no single conceptual apparatus in them. Nevertheless, several important areas can be singled out here too - such as the development of a formal apparatus of inductive logic, methods of morphological analysis and other structural and syntactic methods for constructing new alternatives, syntactic methods and organization of group interaction when solving creative problems, as well as the study of the main paradigms search thinking.

Tasks of the third type consist in constructing a set of simulation models that describe the influence of one or another interaction on the behavior of the object of study. Note that system studies do not pursue the goal of creating a certain supermodel. We are talking about the development of private models, each of which solves its own specific issues.

Even after such simulation models have been created and studied, the question of bringing various aspects of the system's behavior into a single scheme remains open. However, it can and should be solved not by building a supermodel, but by analyzing the reactions to the observed behavior of other interacting objects, i.e. by studying the behavior of objects - analogues and transferring the results of these studies to the object of system analysis. Such a study provides a basis for a meaningful understanding of situations of interaction and the structure of relationships that determine the place of the system under study in the structure of the supersystem, of which it is a component.

Tasks of the fourth type are associated with the construction of decision-making models. Any system study is connected with the study of various alternatives for the development of the system. The task of system analysts is to choose and justify the best development alternative. At the stage of development and decision-making, it is necessary to take into account the interaction of the system with its subsystems, combine the goals of the system with the goals of the subsystems, and single out global and secondary goals.

The most developed and at the same time the most specific area of scientific creativity is associated with the development of the theory of decision making and the formation of target structures, programs and plans. There is no lack of work and actively working researchers here. However, in this case, too many results are at the level of unconfirmed inventions and discrepancies in understanding both the essence of the tasks and the means to solve them. Research in this area includes:

a) building a theory for evaluating the effectiveness of decisions made or plans and programs formed; b) solving the problem of multi-criteria in the evaluation of decision or planning alternatives;

b) study of the problem of uncertainty, especially associated not with statistical factors, but with the uncertainty of expert judgments and deliberately created uncertainty associated with simplifying ideas about the behavior of the system;

c) development of the problem of aggregating individual preferences on decisions affecting the interests of several parties that affect the behavior of the system;

d) study of the specific features of the socio-economic performance criteria;

e) creation of methods for checking the logical consistency of target structures and plans and establishing the necessary balance between the predetermination of the action program and its readiness for restructuring when new information arrives, both about external events and changing ideas about the implementation of this program.

The latter direction requires a new awareness of the real functions of the target structures, plans, programs and the definition of those that they should perform, as well as the connections between them.

The considered tasks of system analysis do not cover the full list of tasks. Listed here are those that present the greatest difficulty in solving them. It should be noted that all the tasks of systemic research are closely interconnected with each other, cannot be isolated and solved separately, both in time and in terms of the composition of performers. Moreover, in order to solve all these problems, the researcher must have a broad outlook and possess a rich arsenal of methods and means of scientific research.

2. Features of system analysis tasks

The ultimate goal of system analysis is to resolve the problem situation that has arisen before the object of the ongoing system research (usually it is a specific organization, team, enterprise, separate region, social structure etc.). System analysis deals with the study of a problem situation, clarification of its causes, development of options for its elimination, decision-making and organization of the further functioning of the system, resolving the problem situation. The initial stage of any system research is the study of the object of the ongoing system analysis, followed by its formalization. At this stage, tasks arise that fundamentally distinguish the methodology of system research from the methodology of other disciplines, namely, a two-pronged task is solved in system analysis. On the one hand, it is necessary to formalize the object of system research, on the other hand, the process of studying the system, the process of formulating and solving the problem, is subject to formalization. Let's take an example from systems design theory. Modern theory computer-aided design of complex systems can be considered as one of the parts of systems research. According to her, the problem of designing complex systems has two aspects. First, it is required to carry out a formalized description of the design object. Moreover, at this stage, the tasks of a formalized description of both the static component of the system (mainly its structural organization is subject to formalization) and its behavior in time (dynamic aspects that reflect its functioning) are solved. Secondly, it is required to formalize the design process. The components of the design process are the methods of forming various design solutions, methods of their engineering analysis and decision-making methods for choosing the best options for implementing the system.

An important place in the procedures of system analysis is occupied by the problem of decision making. As a feature of the tasks facing system analysts, it is necessary to note the requirement for the optimality of the decisions made. At present, it is necessary to solve problems of optimal control of complex systems, optimal design of systems that include a large number of elements and subsystems. The development of technology has reached a level at which the creation of a simply workable design in itself does not always satisfy the leading branches of industry. It is necessary in the course of designing to ensure the best indicators for a number of characteristics of new products, for example, to achieve maximum speed, minimum dimensions, cost, etc. while maintaining all other requirements within the specified limits. Thus, practice requires the development of not just a workable product, object, system, but the creation of an optimal design. Similar reasoning is valid for other activities. When organizing the functioning of an enterprise, requirements are formulated to maximize the efficiency of its activities, the reliability of equipment operation, optimization of system maintenance strategies, resource allocation, etc.

In various fields of practical activity (technology, economics, social sciences, psychology), situations arise when it is required to make decisions for which it is not possible to fully take into account the conditions that determine them. Decision-making in this case will take place under conditions of uncertainty, which has a different nature. One of the simplest types of uncertainty is the uncertainty of the initial information, which manifests itself in various aspects. First of all, we note such an aspect as the impact on the system of unknown factors.

Uncertainty due to unknown factors also comes in different forms. The simplest form of this kind of uncertainty is stochastic uncertainty. It takes place in cases where unknown factors are random variables or random functions, the statistical characteristics of which can be determined based on the analysis of past experience in the functioning of the system research object.

The next type of uncertainty is uncertainty of goals. The formulation of the goal in solving problems of system analysis is one of the key procedures, because the goal is the object that determines the formulation of the problem of system research. The uncertainty of the goal is a consequence of the multicriteria of the problems of system analysis. Assigning a goal, choosing a criterion, formalizing a goal is almost always a difficult problem. Tasks with many criteria are typical for large technical, economic, economic projects.

And, finally, it should be noted such type of uncertainty as the uncertainty associated with the subsequent influence of the results of the decision on the problem situation. The fact is that the decision being made at the moment and implemented in some system is designed to affect the functioning of the system. Actually, for this it is adopted, since, according to the idea of system analysts, this solution should solve the problem situation. However, since the decision is made for a complex system, the development of the system in time can have many strategies. And of course, at the stage of forming a decision and taking a control action, analysts may not have a complete picture of the development of the situation. When making a decision, there are various recommendations for predicting the development of the system over time. One of these approaches recommends predicting some "average" dynamics of the system development and making decisions based on such a strategy. Another approach recommends that when making a decision, proceed from the possibility of realizing the most unfavorable situation.

As the next feature of system analysis, we note the role of models as a means of studying systems that are the object of system research. Any methods of system analysis are based on the mathematical description of certain facts, phenomena, processes. When using the word “model”, they always mean some description that reflects precisely those features of the process under study that are of interest to the researcher. The accuracy and quality of the description are determined, first of all, by the correspondence of the model to the requirements that are imposed on the study, by the correspondence of the results obtained with the help of the model to the observed course of the process. If the language of mathematics is used in the development of the model, they speak of mathematical models. The construction of a mathematical model is the basis of all system analysis. This is the central stage of research or design of any system. The success of all subsequent analysis depends on the quality of the model. However, in systems analysis, along with formalized procedures, informal, heuristic research methods occupy a large place. There are a number of reasons for this. The first is as follows. When building models of systems, there may be a lack or lack of initial information to determine the parameters of the model.

In this case, an expert survey of specialists is carried out in order to eliminate uncertainty or, at least, reduce it, i.e. the experience and knowledge of specialists can be used to assign the initial parameters of the model.

Another reason for using heuristic methods is as follows. Attempts to formalize the processes occurring in the systems under study are always associated with the formulation of certain restrictions and simplifications. Here it is important not to cross the line beyond which further simplification will lead to the loss of the essence of the phenomena described. In other words-

However, the desire to adapt a well-studied mathematical apparatus to describe the phenomena under study can distort their essence and lead to incorrect decisions. In this situation, it is required to use the scientific intuition of the researcher, his experience and ability to formulate the idea of solving the problem, i.e. a subconscious, internal substantiation of algorithms for constructing a model and methods for their study is used, which is not amenable to formal analysis. Heuristic methods for finding solutions are formed by a person or a group of researchers in the course of their creative activity. Heuristics is a set of knowledge, experience, intelligence used to obtain solutions using informal rules. Heuristic methods turn out to be useful and even indispensable in studies that are of a non-numerical nature or are characterized by complexity, uncertainty, and variability.

Surely, when considering specific problems of system analysis, it will be possible to single out some more of their features, but, in the opinion of the author, the features noted here are common to all problems of system research.

3. System analysis procedures

IN previous section three stages of system analysis were formulated. These stages are the basis for solving any problem of conducting systematic research. Their essence is that it is necessary to build a model of the system under study, i.e. give a formalized description of the object under study, formulate a criterion for solving the problem of system analysis, i.e. set a research problem and then solve the problem. These three stages of system analysis are an enlarged scheme for solving the problem. In fact, the tasks of system analysis are quite complex, so the enumeration of the stages cannot be an end in itself. We also note that the system analysis methodology and guidelines are not universal - each study has its own characteristics and requires intuition, initiative and imagination from the performers in order to correctly determine the goals of the project and succeed in achieving them. There have been repeated attempts to create a fairly general, universal algorithm for system analysis. A careful examination of the algorithms available in the literature shows that they have a large degree of generality in general and differences in particulars and details. We will try to outline the main procedures of the algorithm for conducting a system analysis, which are a generalization of the sequence of stages for conducting such an analysis, formulated by a number of authors, and reflect it. general patterns.

We list the main procedures for system analysis:

study of the structure of the system, analysis of its components, identification of relationships between individual elements;

collection of data on the functioning of the system, the study of information flows, observations and experiments on the analyzed system;

building models;

Checking the adequacy of models, analysis of uncertainty and sensitivity;

· study of resource opportunities;

definition of the goals of system analysis;

formation of criteria;

generation of alternatives;

implementation of choice and decision making;

Implementation of the results of the analysis.

4. Determining the goals of system analysis

4.1 Fproblem statement

For traditional sciences, the initial stage of work is the formulation of a formal problem that must be solved. In the study of a complex system, this is an intermediate result, which is preceded by a long work on structuring the original problem. The starting point for setting goals in systems analysis is related to the formulation of the problem. Here we should note the following feature of problems of system analysis. The need for system analysis arises when the customer has already formulated his problem, i.e. the problem not only exists, but also requires a solution. However, the system analyst must be aware that the problem formulated by the customer is an approximate working version. The reasons why the original formulation of the problem should be considered as a first approximation are as follows. The system for which the goal of conducting a system analysis is formulated is not isolated. It is connected with other systems, is part of a certain supersystem, for example, an automated control system for a department or workshop at an enterprise is a structural unit of the automated control system for the entire enterprise. Therefore, when formulating a problem for the system under consideration, it is necessary to take into account how the solution of this problem will affect the systems with which this system is connected. Inevitably, the planned changes will affect both the subsystems that make up this system and the supersystem containing this system. Thus, any real problem should be treated not as a separate one, but as an object from among interrelated problems.

When formulating a system of problems, a systems analyst should follow some guidelines. First, the opinion of the customer should be taken as the basis. As a rule, this is the head of the organization for which the system analysis is being carried out. It is he who, as noted above, generates the original formulation of the problem. Further, the system analyst, having familiarized himself with the formulated problem, must understand the tasks that were set for the leader, the restrictions and circumstances that affect the behavior of the leader, the conflicting goals between which he tries to find a compromise. The systems analyst must study the organization for which the systems analysis is being carried out. Careful consideration should be given to the existing management hierarchy, the functions of the various groups, and previous studies of relevant issues, if any. The analyst must refrain from expressing his preconceived opinion about the problem and from trying to fit it into the framework of his previous ideas in order to use the approach he desires to solve it. Finally, the analyst should not leave the manager's statements and remarks unverified. As already noted, the problem formulated by the leader must, firstly, be expanded to a set of problems agreed with super- and subsystems, and, secondly, it must be coordinated with all interested parties.

It should also be noted that each of the interested parties has its own vision of the problem, attitude towards it. Therefore, when formulating a set of problems, it is necessary to take into account what changes and why one side or the other wants to make. In addition, the problem must be considered comprehensively, including in terms of time and history. It is required to anticipate how the formulated problems may change over time or due to the fact that the study will be of interest to managers at another level. When formulating a set of problems, a systems analyst must know the big picture of who is interested in a particular solution.

4.2 Setting goals

After the problem that needs to be overcome in the course of the system analysis is formulated, they proceed to the definition of the goal. To determine the purpose of system analysis means to answer the question of what needs to be done to remove the problem. To formulate a goal means to indicate the direction in which one should move in order to solve the existing problem, to show the ways that lead away from the existing problem situation.

When formulating a goal, it is always necessary to be aware that it plays an active role in management. In the definition of the goal, it was reflected that the goal is the desired result of the development of the system. Thus, the formulated goal of system analysis will determine the entire further complex of works. Therefore, goals must be realistic. Setting realistic goals will direct all the activities of performing a systems analysis to obtain a certain useful result. It is also important to note that the idea of the goal depends on the stage of cognition of the object, and as ideas about it develop, the goal can be reformulated. Changing goals over time can occur not only in form, due to a better understanding of the essence of the phenomena occurring in the system under study, but also in content, due to changes in objective conditions and subjective attitudes that affect the choice of goals. The timing of changing ideas about goals, aging goals are different and depend on the level of the hierarchy of the object. Higher level targets are more durable. The dynamism of goals should be taken into account in the system analysis.

When formulating the goal, it is necessary to take into account that the goal is influenced by both external factors in relation to the system and internal ones. At the same time, internal factors are the same objectively influencing the process of goal formation as external factors.

Further, it should be noted that even at the highest level of the hierarchy of the system, there is a plurality of goals. When analyzing the problem, it is necessary to take into account the goals of all interested parties. Among the many goals, it is desirable to try to find or form a global goal. If this fails, you should rank the targets in order of their preference to remove the problem in the analyzed system.

The study of the goals of persons interested in the problem should provide for the possibility of clarifying, expanding or even replacing them. This circumstance is the main reason for the iterative nature of system analysis.

The choice of the goals of the subject is decisively influenced by the value system that he adheres to, therefore, when forming goals, the necessary stage of work is to identify the value system that the decision maker adheres to. For example, a distinction is made between technocratic and humanistic value systems. According to the first system, nature is proclaimed as a source of inexhaustible resources, man is the king of nature. Everyone knows the thesis: “We cannot expect favors from nature. It is our task to take them from her.” The humanistic value system says that natural resources are limited, that a person must live in harmony with nature, and so on. The practice of the development of human society shows that following the technocratic value system leads to disastrous consequences. On the other hand, a complete rejection of technocratic values also has no justification. It is necessary not to oppose these systems, but to reasonably supplement them and formulate the goals for the development of the system, taking into account both systems of values.

5. Generation of alternatives

The next stage of system analysis is the creation of many possible ways to achieve the formulated goal. In other words, at this stage it is necessary to generate a set of alternatives, from which the choice of the best path for the development of the system will then be made. This stage of system analysis is very important and difficult. Its importance lies in the fact that the ultimate goal of system analysis is to choose the best alternative on a given set and to justify this choice. If the best one is not included in the formed set of alternatives, then no most advanced methods of analysis will help to calculate it. The difficulty of the stage is due to the need to generate a sufficiently complete set of alternatives, including, at first glance, even the most unrealizable ones.

Generation of alternatives, i.e. ideas about possible ways achieving a goal is a real creative process. There are a number of recommendations on possible approaches to the implementation of the procedure in question. Must be generated as soon as possible more alternatives. The following generation methods are available:

a) search for alternatives in patent and journal literature;

b) involvement of several experts with different training and experience;

c) an increase in the number of alternatives due to their combination, the formation of intermediate options between those proposed earlier;

d) modification of an existing alternative, i.e. the formation of alternatives that are only partially different from the known;

e) inclusion of alternatives opposite to those proposed, including the “zero” alternative (do nothing, i.e. consider the consequences of the development of events without the intervention of system engineers);

f) stakeholder interviews and broader questionnaires; g) inclusion in the consideration of even those alternatives that at first glance seem far-fetched;

g) generation of alternatives calculated for different time intervals (long-term, short-term, emergency).

When performing work on generating alternatives, it is important to create favorable conditions for employees performing this type of activity. Of great importance are psychological factors that affect the intensity of creative activity, so it is necessary to strive to create a favorable climate in the workplace of employees.

There is another danger that arises when performing work on the formation of a variety of alternatives, which must be mentioned. If we specifically strive to ensure that as many alternatives as possible are obtained at the initial stage, i.e. try to make the set of alternatives as complete as possible, then for some problems their number can reach many tens. A detailed study of each of them will require an unacceptably large investment of time and money. Therefore, in this case, it is necessary to conduct a preliminary analysis of alternatives and try to narrow the set in the early stages of the analysis. At this stage of the analysis, qualitative methods comparison of alternatives without resorting to more precise quantitative methods. In this way, coarse screening is carried out.

We now present the methods used in system analysis to carry out work on the formation of a set of alternatives.

6. Implementation of analysis results

System analysis is an applied science, its ultimate goal is to change the existing situation in accordance with the set goals. The final judgment on the correctness and usefulness of system analysis can only be made on the basis of the results of its practical application.

The final result will depend not only on how perfect and theoretically substantiated the methods used in the analysis, but also on how competently and efficiently the received recommendations are implemented.

Currently, increased attention is paid to the issues of introducing the results of system analysis into practice. In this direction, the works of R. Ackoff can be noted. It should be noted that the practice of system research and the practice of implementing their results differ significantly for systems different types. According to the classification, systems are divided into three types: natural, artificial and sociotechnical. In systems of the first type, connections are formed and act in a natural way. Examples of such systems are ecological, physical, chemical, biological, etc. systems. In systems of the second type, connections are formed as a result human activity. Examples are all sorts of technical systems. In systems of the third type, in addition to natural connections, interpersonal connections play an important role. Such connections are not determined by the natural properties of objects, but by cultural traditions, the upbringing of the subjects participating in the system, their character and other features.

System analysis is used to study systems of all three types. Each of them has its own characteristics that require consideration when organizing work to implement the results. The share of semi-structured problems is greatest in systems of the third type. Consequently, the practice of implementing the results of system research in these systems is the most difficult.

When implementing the results of system analysis, it is necessary to keep in mind the following circumstance. The work is carried out for the client (customer), who has the power sufficient to change the system in the ways that will be determined as a result of the system analysis. All stakeholders should be directly involved in the work. Stakeholders are those who are responsible for solving the problem and those who are directly affected by the problem. As a result of the introduction of system research, it is necessary to ensure the improvement of the work of the customer's organization from the point of view of at least one of the interested parties; at the same time, deterioration of this work from the point of view of all other participants in the problem situation is not allowed.

Speaking about the implementation of the results of system analysis, it is important to note that in real life the situation when research is first carried out, and then their results are put into practice, is extremely rare, only in cases where we are talking about simple systems. In the study of sociotechnical systems, they change over time both by themselves and under the influence of research. In the process of conducting a system analysis, the state of the problem situation, the goals of the system, the personal and quantitative composition of the participants, the relationship between stakeholders change. In addition, it should be noted that the implementation of the decisions made affects all factors of the system functioning. The stages of research and implementation in this type of systems actually merge, i.e. is an iterative process. The ongoing research has an impact on the life of the system, and this modifies the problem situation and poses a new research task. A new problematic situation stimulates further system analysis, etc. Thus, the problem is gradually solved in the course of active research.

INconclusion

An important feature of system analysis is the study of goal formation processes and the development of means for working with goals (methods, structuring goals). Sometimes even systems analysis is defined as a methodology for studying purposeful systems.

Bibliography

Moiseev, N.N. Mathematical problems of system analysis / N.N. Moiseev. - M.: Nauka, 1981.

Optner, S. System analysis for solving business and industrial problems / S. Optner. - M.: Soviet radio,

Fundamentals of the system approach and their application to the development of territorial ACS / ed. F.I. Peregudov. - Tomsk: Publishing House of TSU, 1976. - 440 p.

Fundamentals of the general theory of systems: textbook. allowance. - St. Petersburg. : VAS, 1992. - Part 1.

Peregudov, F.I. Introduction to system analysis: textbook. allowance / F.I. Peregudov, F.P. Tarasenko. - M.: Higher School, 1989. - 367 p.

Rybnikov, K.A. History of mathematics: textbook / K.A. Rybnikov. - M. : Publishing House of Moscow State University, 1994. - 496 p.

Stroyk, D.Ya. Brief essay on the history of mathematics / D.Ya. Stroyk. - M. : Nauka, 1990. - 253 p.

Stepanov, Yu.S. Semiotics / Yu.S. Stepanov. - M. : Nauka, 1971. - 145 p.

Theory of systems and methods of system analysis in management and communication / V.N. Volkova, V.A. Voronkov, A.A. Denisov and others -M. : Radio and communication, 1983. - 248 p.

Hosted on Allbest.ru

...

Send your good work in the knowledge base is simple. Use the form below

Students, graduate students, young scientists who use the knowledge base in their studies and work will be very grateful to you.

Hosted at http://www.allbest.ru/

Introduction

1. System analysis

Conclusion

Bibliography

Introduction

From a practical point of view, system analysis is a universal technique for solving complex problems of an arbitrary nature, where the concept of "problem" is defined as "a subjective negative attitude of the subject to reality." The difficulty in diagnosing a problem is partly due to the fact that the subject may not have special knowledge and therefore is not able to adequately interpret the results of a study conducted by a systems analyst.

Systems analysis eventually became an inter- and trans-disciplinary course, summarizing the methodology for studying complex technical and social systems.

With the growth of the population on the planet, the acceleration of scientific and technological progress, the threat of hunger, unemployment and various environmental disasters, the application of systems analysis becomes more and more important.

Western authors (J. van Gig, R. Ashby, R. Ackoff, F. Emery, S. Beer) are mostly inclined towards applied systems analysis, its application to the analysis and design of organizations. The classics of Soviet system analysis (A.I. Uemov, M.V. Blauberg, E.G. Yudin, Yu.A. Urmantsev, etc.) pay more attention to the theory of system analysis, as a framework for increasing scientific knowledge, to the definition philosophical categories"system", "element", "part", "whole", etc.

System analysis requires further study of the features and patterns of self-organizing systems; development of an informational approach based on dialectical logic; an approach based on the gradual formalization of decision-making models based on a combination of formal methods and techniques; formation of the theory of system-structural synthesis; development of methods for organizing complex examinations.

The development of the topic "system analysis" is quite large: many scientists, researchers, and philosophers have been involved in the concept of systemicity. However, it can be noted that there is an insufficient number of complete and explicit theories for studying the subject of its application in management.

The object of research work is system analysis, and the subject is the study and analysis of the evolution of system analysis in theory and practice.

The purpose of the work is to identify the main stages in the development and formation of system analysis.

This goal necessitates the solution of the following main tasks:

To study the history of development and change of system analysis;

Consider the methodology of system analysis;

To study and analyze the possibilities of implementing system analysis.

1. System analysis

1.1 Definitions of systems analysis

System analysis as a discipline was formed as a result of the need to explore and design complex systems, manage them in conditions of incomplete information, limited resources and time pressure.

Systems analysis is a further development of a number of disciplines, such as operations research, optimal control theory, decision theory, expert analysis, systems management theory, etc. To successfully solve the tasks set, system analysis uses the entire set of formal and informal procedures. The listed theoretical disciplines are the basis and methodological basis of system analysis. Thus, system analysis is an interdisciplinary course that generalizes the methodology for studying complex technical, natural and social systems. The widespread dissemination of ideas and methods of system analysis, and most importantly, their successful application in practice, became possible only with the introduction and widespread use of computers. Akoff, R. On Purposeful Systems / R. Akoff, F. Emery. - M.: Soviet radio, 2008. - 272 p. It was the use of computers as a tool for solving complex problems that made it possible to move from constructing theoretical models of systems to their wide practical application. In this regard, N.N. Moiseev writes that system analysis is a set of methods based on the use of computers and focused on the study of complex systems - technical, economic, environmental, etc. The central problem of system analysis is the problem of decision making.

In relation to the problems of research, design and management of complex systems, the decision-making problem is associated with the choice of a certain alternative under conditions of various kinds of uncertainty. Uncertainty is due to the multicriteria of optimization problems, the uncertainty of the goals of system development, the ambiguity of system development scenarios, the lack of a priori information about the system, the impact of random factors during the dynamic development of the system, and other conditions. Given these circumstances, systems analysis can be defined as a discipline dealing with decision-making problems in conditions where the choice of an alternative requires the analysis of complex information of various physical nature. Volkova, V.N. System analysis and its application in automated control systems / V.N. Volkova, A.A. Denisov. - L.: LPI, 2008. - 83 p.

System analysis is a synthetic discipline. It can be divided into three main directions. These three directions correspond to three stages that are always present in the study of complex systems:

1) building a model of the object under study;

2) setting the research problem;

3) solution of the set mathematical problem.

Let's consider these steps.

Since knowledge is always relative, the description in any language reflects only some aspects of the ongoing processes and is never absolutely complete. On the other hand, it should be noted that when building a model, it is necessary to focus on those aspects of the process under study that are of interest to the researcher. It is deeply erroneous to want to reflect all aspects of the system's existence when building a system model. When conducting a system analysis, as a rule, they are interested in the dynamic behavior of the system, and when describing the dynamics from the point of view of the study, there are paramount parameters and interactions, and there are parameters that are not essential in this study. Thus, the quality of the model is determined by the correspondence of the description to the requirements that apply to the study, the correspondence of the results obtained with the help of the model to the course of the observed process or phenomenon. The construction of a mathematical model is the basis of all system analysis, the central stage of research or design of any system. The result of the entire system analysis depends on the quality of the model. Bertalanfi L. Fon. General Systems Theory: A Critical Review / Bertalanfi L. Fon // Studies in General Systems Theory. - M.: Progress, 2009. - S. 23 - 82.

Statement of the research problem

By analyzing the system requirements, i.e. the goals that the researcher intends to achieve, and the uncertainties that are inevitably present, the researcher must formulate the goal of the analysis in the language of mathematics. The optimization language turns out to be natural and convenient here, but by no means the only possible one.

Solution of the stated mathematical problem

Only this third stage of the analysis can be properly attributed to the stage that makes full use of mathematical methods. Although without knowledge of mathematics and the capabilities of its apparatus, the successful implementation of the first two stages is impossible, since formalization methods should be widely used both when building a system model and when formulating the goals and objectives of analysis. However, we note that it is at the final stage of system analysis that subtle mathematical methods may be required. But it should be borne in mind that the problems of system analysis can have a number of features that lead to the need to use heuristic approaches along with formal procedures. The reasons for turning to heuristic methods are primarily related to the lack of a priori information about the processes occurring in the analyzed system. Also, such reasons include the large dimension of the vector x and the complexity of the structure of the set G. In this case, the difficulties arising from the need to use informal analysis procedures are often decisive. Successful solution of problems of system analysis requires the use of informal reasoning at each stage of the study. In view of this, checking the quality of the solution, its compliance with the original goal of the study turns into the most important theoretical problem.

1.2 Characteristics of the tasks of system analysis

System analysis is currently at the forefront of scientific research. It is intended to provide a scientific apparatus for the analysis and study of complex systems. The leading role of system analysis is due to the fact that the development of science has led to the formulation of the tasks that system analysis is designed to solve. The peculiarity of the current stage is that system analysis, having not yet managed to form into a full-fledged scientific discipline, is forced to exist and develop in conditions when society begins to feel the need to apply still insufficiently developed and tested methods and results and is not able to postpone decisions related to them tasks for tomorrow. This is the source of both strength and weakness of system analysis: strength - because it constantly feels the impact of the need for practice, is forced to continuously expand the range of objects of study, and does not have the ability to abstract from the real needs of society; weaknesses - because often the use of "raw", insufficiently developed methods of systematic research leads to the adoption of hasty decisions, the neglect of real difficulties. Clear, D. Systemology / D. Clear. - M.: Radio and communication, 2009. - 262 p.

Let's consider the main tasks, the solution of which is directed by the efforts of specialists and which need further development. First, it should be noted the tasks of studying the system of interactions of the analyzed objects with the environment. The solution to this problem involves:

Drawing a boundary between the system under study and the environment, which predetermines the maximum depth of influence of the interactions under consideration, which limits the consideration;

Determining the real resources of such interaction;

Consideration of the interactions of the system under study with a higher level system.

Tasks of the following type are associated with the design of alternatives for this interaction, alternatives for the development of the system in time and space. An important direction in the development of systems analysis methods is associated with attempts to create new possibilities for constructing original solution alternatives, unexpected strategies, unusual ideas and hidden structures. In other words, we are talking here about the development of methods and means of strengthening the inductive capabilities of human thinking, in contrast to its deductive capabilities, which, in fact, are aimed at the development of formal logical means. Research in this direction has begun only quite recently, and there is still no single conceptual apparatus in them. Nevertheless, several important areas can be singled out here too - such as the development of a formal apparatus of inductive logic, methods of morphological analysis and other structural and syntactic methods for constructing new alternatives, methods of syntectics and organization of group interaction in solving creative problems, as well as the study of the main paradigms search thinking.

Tasks of the third type consist in constructing a set of simulation models that describe the influence of one or another interaction on the behavior of the object of study. It should be noted that system studies do not pursue the goal of creating some kind of supermodel. We are talking about the development of private models, each of which solves its own specific issues.

Such a study provides a basis for a meaningful understanding of situations of interaction and the structure of relationships that determine the place of the system under study in the structure of the supersystem, of which it is a component.

a) building a theory for evaluating the effectiveness of decisions made or plans and programs formed;

b) solving the problem of multi-criteria in the evaluation of decision or planning alternatives;

c) study of the problem of uncertainty, especially associated not with statistical factors, but with the uncertainty of expert judgments and deliberately created uncertainty associated with simplifying ideas about the behavior of the system;

d) development of the problem of aggregating individual preferences on decisions affecting the interests of several parties that affect the behavior of the system;

e) study of specific features of socio-economic criteria of efficiency;

f) creation of methods for checking the logical consistency of target structures and plans and establishing the necessary balance between the predetermination of the action program and its readiness for restructuring when new information arrives, both about external events and changing ideas about the implementation of this program.

The latter direction requires a new awareness of the real functions of the target structures, plans, programs and the definition of those that they should perform, as well as the links between them.

The ultimate goal of system analysis is to resolve the problem situation that has arisen before the object of the ongoing system research (usually it is a specific organization, team, enterprise, separate region, social structure, etc.). System analysis deals with the study of a problem situation, clarification of its causes, development of options for its elimination, decision-making and organization of the further functioning of the system, resolving the problem situation. The initial stage of any system research is the study of the object of the ongoing system analysis, followed by its formalization. At this stage, tasks arise that fundamentally distinguish the methodology of system research from the methodology of other disciplines, namely, a two-pronged task is solved in system analysis. On the one hand, it is necessary to formalize the object of system research, on the other hand, the process of studying the system, the process of formulating and solving the problem, is subject to formalization. Let's take an example from systems design theory. The modern theory of computer-aided design of complex systems can be considered as one of the parts of system research. According to her, the problem of designing complex systems has two aspects. First, it is required to carry out a formalized description of the design object. Moreover, at this stage, the tasks of a formalized description of both the static component of the system (mainly its structural organization is subject to formalization) and its behavior in time (dynamic aspects that reflect its functioning) are solved. Secondly, it is required to formalize the design process. The components of the design process are the methods of forming various design solutions, methods of their engineering analysis and decision-making methods for choosing the best options for implementing the system.

Decision-making in this case will take place under conditions of uncertainty, which has a different nature.

One of the simplest types of uncertainty is the uncertainty of the initial information, which manifests itself in various aspects. First of all, we note such an aspect as the impact on the system of unknown factors.

Uncertainty due to unknown factors also comes in different forms. The simplest type of this kind of uncertainty is stochastic uncertainty. It takes place in cases where unknown factors are random variables or random functions, the statistical characteristics of which can be determined based on the analysis of past experience in the functioning of the system research object.

The next type of uncertainty is the uncertainty of goals. The formulation of the goal in solving problems of system analysis is one of the key procedures, because the goal is the object that determines the formulation of the problem of system research. The uncertainty of the goal is a consequence of the multicriteria of the problems of system analysis.

Assigning a goal, choosing a criterion, formalizing a goal is almost always a difficult problem. Tasks with many criteria are typical for large technical, economic, economic projects.

And, finally, it should be noted such type of uncertainty as the uncertainty associated with the subsequent influence of the results of the decision on the problem situation. The fact is that the decision being made at the moment and implemented in some system is designed to affect the functioning of the system. Actually, for this it is adopted, since, according to the idea of system analysts, this solution should solve the problem situation. However, since the decision is made for a complex system, the development of the system in time can have many strategies. And, of course, at the stage of making a decision and taking a control action, analysts may not have a complete picture of the development of the situation. Anfilatov, V.S. System analysis in management: textbook. allowance / V.S. Anfilatov and others; ed. A.A. Emelyanov. - M.: Finance and statistics, 2008. - 368 p.

analysis system technical natural social

2. The concept of "problem" in systems analysis

System analysis from a practical point of view is a universal technique for solving complex problems of an arbitrary nature. The key concept in this case is the concept of "problem", which can be defined as "the subjective negative attitude of the subject to reality". Accordingly, the stage of identifying and diagnosing a problem in complex systems is the most important, since it determines the goals and objectives of conducting a system analysis, as well as methods and algorithms that will be applied in the future with decision support. At the same time, this stage is the most complex and least formalized.

An analysis of Russian-language works on system analysis allows us to single out the two largest areas in this area, which can be conditionally called rational and objective-subjective approaches.

The first direction (rational approach) considers system analysis as a set of methods, including methods based on the use of computers, focused on the study of complex systems. With this approach, the greatest attention is paid to formal methods for constructing system models and mathematical methods for studying the system. The concepts of "subject" and "problem" as such are not considered, but the concept of "typical" systems and problems is often encountered (management system - management problem, financial system - financial problems, etc.).

With this approach, a "problem" is defined as a discrepancy between the actual and the desired, i.e., a discrepancy between the actually observed system and the "ideal" model of the system. It is important to note that in this case the system is defined solely as that part of objective reality that must be compared with the reference model.

If we rely on the concept of "problem", then we can conclude that when rational approach the problem arises only for a system analyst who has a certain formal model of some system, finds this system and discovers a discrepancy between the model and the real system, which causes his “negative attitude to reality”. Volkova, V.N. System analysis and its application in automated control systems / V.N. Volkova, A.A. Denisov. - L.: LPI, 2008. - 83 p.

Obviously, there are systems whose organization and behavior is strictly regulated and recognized by all subjects - these are, for example, legal laws. The discrepancy between the model (law) and reality in this case is a problem (offence) that needs to be solved. However, there are no strict regulations for most artificial systems, and the subjects have their own personal goals in relation to such systems, which rarely coincide with the goals of other subjects. Moreover, a particular subject has his own idea of which system he is a part of, with which systems he interacts. The concepts with which the subject operates can radically differ from the "rational" generally accepted ones. For example, a subject may not single out a control system from the environment at all, but use some model of interaction with the world that is understandable and convenient only for him. It turns out that the imposition of generally accepted (even if rational) models can lead to the emergence of a “negative attitude” in the subject, and hence to the emergence of new problems, which fundamentally contradicts the very essence of system analysis, which involves an improving impact - when at least one participant in the problem will get better and no one will get worse.

Very often, the formulation of the problem of system analysis in a rational approach is expressed in terms of an optimization problem, i.e., the problem situation is idealized to a level that allows the use of mathematical models and quantitative criteria to determine the best the best option problem resolution.

As is known, for a systemic problem there is no model that exhaustively establishes cause-and-effect relationships between its components, therefore the optimization approach seems not quite constructive: “... the theory of system analysis proceeds from the absence of an optimal, absolutely best option for resolving problems of any nature ... the search for a realistically achievable (compromise) option for resolving the problem, when the desired can be sacrificed for the sake of the possible, and the boundaries of the possible can be significantly expanded due to the desire to achieve the desired. This assumes the use of situational preference criteria, i.e., criteria that are not initial settings, but are developed in the course of the study ... ”.

Another direction of system analysis - an objective-subjective approach, based on the works of Ackoff, puts the concept of the subject and the problem at the head of system analysis. In fact, in this approach, we include the subject in the definition of the existing and ideal system, i.e. on the one hand, system analysis proceeds from the interests of people - it introduces a subjective component of the problem, on the other hand, it explores objectively observable facts and patterns.

Let's go back to the definition of "problem". From it, in particular, it follows that when we observe irrational (in the generally accepted sense) behavior of the subject, and the subject does not have a negative attitude to what is happening, then there is no problem that needs to be solved. This fact although it does not contradict the concept of "problem", but in certain situations it is impossible to exclude the possibility of the existence of an objective component of the problem.

System analysis has in its arsenal the following possibilities to solve the problem of the subject:

* intervene in objective reality and, having eliminated the objective part of the problem, change the subjective negative attitude of the subject,

* change the subjective attitude of the subject without interfering with reality,

* simultaneously intervene in objective reality and change the subjective attitude of the subject.

Obviously, the second method does not solve the problem, but only eliminates its influence on the subject, which means that the objective component of the problem remains. The opposite situation is also true, when the objective component of the problem has already manifested itself, but the subjective attitude has not yet been formed, or for a number of reasons it has not yet become negative.

Here are several reasons why the subject may not have a “negative attitude to reality”: Director, S. Introduction to Systems Theory / S. Director, D. Rohrar. - M.: Mir, 2009. - 286 p.

* has incomplete information about the system or does not use it completely;

* changes the assessment of relationships with the environment at the mental level;

* interrupts the relationship with the environment, which caused a "negative attitude";

* does not believe information about the existence of problems and their nature, because believes that the people reporting it denigrate his activities or pursue their own selfish interests, and perhaps because they simply do not personally love these people.

It should be remembered that in the absence of a negative attitude of the subject, the objective component of the problem remains and continues to influence the subject to one degree or another, or the problem may significantly worsen in the future.

Since the identification of a problem requires an analysis of a subjective attitude, this stage belongs to the non-formalizable stages of a system analysis.

No effective algorithms or techniques have been proposed so far, most often the authors of works on system analysis rely on the experience and intuition of the analyst and offer him complete freedom of action.

A system analyst must have a sufficient set of tools to describe and analyze that part of objective reality with which the subject interacts or can interact. Tools may include methods for experimental study of systems and their modeling. With the widespread introduction of modern information technologies in organizations (commercial, scientific, medical, etc.), almost every aspect of their activities is recorded and stored in databases that already today have very large volumes. Information in such databases contains a detailed description of both the systems themselves and the history of their (systems) development and life. It can be said that today, when analyzing most artificial systems, an analyst is more likely to encounter a lack of effective methods for studying systems than a lack of information about the system.

However, the subjective attitude must be formulated by the subject, and he may not have special knowledge and therefore is not able to adequately interpret the results of the research conducted by the analyst. Therefore, knowledge about the system and predictive models, which the analyst will eventually receive, must be presented in an explicit, interpretable form (possibly in natural language). Such a representation can be called knowledge about the system under study.

Unfortunately, there are currently no effective methods for obtaining knowledge about the system. Of greatest interest are the models and algorithms of Data Mining (intelligent data analysis), which are used in private applications to extract knowledge from "raw" data. It is worth noting that Data Mining is an evolution of the theory of database management and online data analysis (OLAP), based on the idea of a multidimensional conceptual representation.

But in last years Due to the growing problem of “information overload”, more and more researchers are using and improving Data Mining methods to solve knowledge extraction problems.

The widespread use of knowledge extraction methods is very difficult, which, on the one hand, is due to the insufficient effectiveness of most of the known approaches, which are based on fairly formal mathematical and statistical methods, and, on the other hand, to the difficulty of using effective methods of intellectual technologies that do not have a sufficient formal description and require attracting expensive specialists. The latter can be overcome by using a promising approach to building an effective system for analyzing data and extracting knowledge about the system, based on the automated generation and configuration of intelligent information technologies. This approach will allow, firstly, through the use of advanced intellectual technologies, to significantly increase the efficiency of solving the problem of extracting knowledge that will be presented to the subject at the stage of identifying the problem in system analysis. Secondly, to eliminate the need for a setup specialist and the use of intelligent technologies, since the latter will be generated and configured automatically. Bertalanfi L. Fon. History and status of general systems theory / Bertalanfi L. Fon // System Research: Yearbook. - M.: Nauka, 2010. - C. 20 - 37.

Conclusion

The formation of systems analysis is associated with the middle of the twentieth century, but in fact it began to be used much earlier. It is in economics that its use is associated with the name of the theorist of capitalism K. Marx.

Today, this method can be called universal - system analysis is used in the management of any organization. Its value in management activities it's hard not to overestimate. Management from the standpoint of a system approach is the implementation of a set of influences on an object to achieve a given goal, based on information about the behavior of the object and the state of the external environment. System analysis allows you to take into account the difference in the socio-cultural characteristics of the people who work in the company, and the cultural traditions of the society in which the organization operates. Managers can more easily align their specific work with that of the organization as a whole if they understand the system and their role in it.

The disadvantages of system analysis include the fact that consistency means certainty, consistency, integrity, and in real life this is not observed. But these principles apply to any theory, and this does not make them vague or inconsistent. In theory, each researcher must find the basic principles and adjust them depending on the situation. Within the framework of the system, one can also single out the problems of copying a strategy or even a technique for its formation, which can work in one company and be completely useless in another.

System analysis has been improved in the process of development, and the scope of its application has also changed. On its basis, control tasks were developed in several directions.

Bibliography

1. Ackoff, R. Fundamentals of Operations Research / R. Ackoff, M. Sassienne. - M.: Mir, 2009. - 534 p.

2. Akoff, R. On Purposeful Systems / R. Akoff, F. Emery. - M.: Soviet radio, 2008. - 272 p.

3. Anokhin, P.K. Selected Works: Philosophical Aspects of Systems Theory / P.K. Anokhin. - M.: Nauka, 2008.

4. Anfilatov, V.S. System analysis in management: textbook. allowance / V.S. Anfilatov and others; ed. A.A. Emelyanov. - M.: Finance and statistics, 2008. - 368 p.

5. Bertalanffy L. Fon. History and status of general systems theory / Bertalanfi L. Fon // System Research: Yearbook. - M.: Nauka, 2010. - C. 20 - 37.

6. Bertalanffy L. Fon. General Systems Theory: A Critical Review / Bertalanfi L. Fon // Studies in General Systems Theory. - M.: Progress, 2009. - S. 23 - 82.

7. Bogdanov, A.A. General organizational science: textology: in 2 books. / A.A. Bogdanov. - M., 2005

8. Volkova, V.N. Fundamentals of systems theory and system analysis: a textbook for universities / V.N. Volkova, A.A. Denisov. - 3rd ed. - St. Petersburg: Publishing house of St. Petersburg State Technical University, 2008.

9. Volkova, V.N. System analysis and its application in automated control systems / V.N. Volkova, A.A. Denisov. - L.: LPI, 2008. - 83 p.

10. Voronov, A.A. Fundamentals of the theory of automatic control / A.A. Voronov. - M.: Energy, 2009. - T. 1.

11. Director, S. Introduction to Systems Theory / S. Director, D. Rohrar. - M.: Mir, 2009. - 286 p.

12. Clear, D. Systemology / D. Clear. - M.: Radio and communication, 2009. - 262 p.

Hosted on Allbest.ru

Send your good work in the knowledge base is simple. Use the form below

Students, graduate students, young scientists who use the knowledge base in their studies and work will be very grateful to you.

Introduction 2

1. The essence of the system approach as the basis of system analysis 5

1.1 Content and characteristics of the systems approach 5

1.2 Basic principles of the systems approach 8

2.Basic elements of system analysis 11

2. 1 Conceptual apparatus of system analysis 11
2. 2 Principles of system analysis 15
2. 3 Methods of system analysis 20

Conclusion 29
Literature 31
Introduction
In the conditions of the dynamism of modern production and society, management must be in a state of continuous development, which today cannot be achieved without researching trends and opportunities, without choosing alternatives and directions for development, performing management functions and methods of making managerial decisions. The development and improvement of the enterprise is based on a thorough and deep knowledge of the activities of the organization, which requires a study of management systems.
Research is carried out in accordance with the chosen goal and in a certain sequence. Research is an integral part of the organization's management and is aimed at improving the main characteristics of the management process. When conducting research on control systems, the object of study is the control system itself, which is characterized by certain features and subject to a number of requirements.
The effectiveness of the study of control systems is largely determined by the chosen and used research methods. Research methods are methods, techniques for conducting research. Their competent application contributes to obtaining reliable and complete results of the study of problems that have arisen in the organization. The choice of research methods, the integration of various methods in the conduct of research is determined by the knowledge, experience and intuition of the specialists conducting the research.
System analysis is used to identify the specifics of the work of organizations and develop measures to improve production and economic activities. The main goal of system analysis is the development and implementation of such a control system, which is chosen as a reference system that best meets all the requirements of optimality. System analysis is complex in nature and is based on a set of approaches, the use of which will make it possible to carry out the analysis in the best way and obtain the desired results. For successful analysis, it is necessary to select a team of specialists who are familiar with the methods economic analysis and organization of production.
Trying to understand a system of great complexity, consisting of many diverse in characteristics and in turn complex subsystems, scientific knowledge goes the way of differentiation, studying the subsystems themselves and ignoring their interaction with the large system in which they are included and which has a decisive impact on the entire global system as a whole. But complex systems are not reducible to the simple sum of their parts; to understand the integrity, its analysis must certainly be supplemented by a deep systemic synthesis; an interdisciplinary approach and interdisciplinary research are needed here, and a completely new scientific toolkit is needed.
The relevance of the chosen topic of the course work lies in the fact that in order to comprehend the laws governing human activity, it is important to learn how to understand how in each case the general context for the perception of the next tasks is formed, how to bring into the system (hence the name - “system analysis”) initially disparate and redundant information about the problem situation, how to coordinate with each other and derive one from the other representations and goals of different levels related to a single activity.
Here lies a fundamental problem that affects almost the very foundations of the organization of any human activity. The same task in a different context, at different levels of decision-making, requires completely different ways of organizing and different knowledge. During the transition, as the action plan is concretized from one level to another, the formulations of both the main goals and the main principles on which their achievement is based are radically transformed. And finally, at the stage of distribution of limited common resources between individual programs, one has to compare the fundamentally incomparable, since the effectiveness of each of the programs can only be assessed according to some one of its own criteria.
A systematic approach is one of the most important methodological principles modern science and practices. System analysis methods are widely used to solve many theoretical and applied problems.
The main objectives of the course work is to study the essence of a systematic approach, as well as the basic principles and methods of system analysis.
1. The essence of the system approach as the basis of system analysis

1 Content and characteristics of a systematic approach

Starting from the middle of the 20th century. intensive developments are being carried out in the field of the systems approach and general systems theory. The systematic approach developed, solving a triune task: accumulation in general scientific concepts and concepts of the latest results of social, natural and technical sciences concerning the systemic organization of objects of reality and methods of their cognition; integration of the principles and experience of the development of philosophy, primarily the results of the development of the philosophical principle of consistency and related categories; application of the conceptual apparatus and modeling tools developed on this basis to solve urgent complex problems.

SYSTEM APPROACH - a methodological direction in science, the main task of which is to develop methods for researching and constructing complex objects - systems of various types and classes. A systematic approach is a certain stage in the development of methods of cognition, methods of research and design activities, ways of describing and explaining the nature of analyzed or artificially created objects.

At present, a systematic approach is increasingly used in management, experience is accumulating in building system descriptions of research objects. The need for a systematic approach is due to the enlargement and complexity of the systems under study, the need to manage large systems and integrate knowledge.

"System" is a Greek word (systema), literally meaning a whole made up of parts; a set of elements that are in relationships and connections with each other and form a certain integrity, unity.

Other words can be formed from the word "system": "systemic", "systematize", "systematic". In a narrow sense, we understand the system approach as the application of system methods to study real physical, biological, social, and other systems.

The systems approach in a broad sense includes, in addition, the application of system methods for solving the problems of systematics, planning and organizing a complex and systematic experiment.

The term "system approach" covers a group of methods by which a real object is described as a set of interacting components. These methods are developed within the framework of individual scientific disciplines, interdisciplinary syntheses and general scientific concepts.

The general tasks of systems research are the analysis and synthesis of systems. In the process of analysis, the system is isolated from the environment, its composition is determined,
structures, functions, integral characteristics (properties), as well as system-forming factors and relationships with the environment.

In the process of synthesis, a model of a real system is created, the level of an abstract description of the system rises, the completeness of its composition and structures, the bases of the description, the laws of dynamics and behavior are determined.

The system approach is applied to sets of objects, individual objects and their components, as well as to the properties and integral characteristics of objects.

The systems approach is not an end in itself. In each case, its use should give a real, quite tangible effect. The system approach allows one to see gaps in knowledge about a given object, to detect their incompleteness, to determine the tasks of scientific research, in some cases - by interpolation and extrapolation - to predict the properties of the missing parts of the description. There are several types of systems approach: integrated, structural, holistic.

It is necessary to define the scope of these concepts.

An integrated approach suggests the presence of a set of object components or applied research methods. At the same time, neither the relations between objects, nor the completeness of their composition, nor the relations of the components as a whole are taken into account. Mainly the problems of statics are solved: the quantitative ratio of components and the like.

The structural approach suggests studying the composition (subsystems) and structures of an object. With this approach, there is still no correlation between subsystems (parts) and the system (whole). Decomposition of systems into subsystems is not carried out in a unified way. The dynamics of structures, as a rule, is not considered.

With a holistic approach, relationships are studied not only between parts of an object, but also between parts and the whole. The decomposition of the whole into parts is unique. So, for example, it is customary to say that "the whole is that from which nothing can be taken away and to which nothing can be added." The holistic approach proposes the study of the composition (subsystems) and structures of an object not only in statics, but also in dynamics, i.e., it proposes the study of the behavior and evolution of systems. a holistic approach is not applicable to all systems (objects). but only those with a high degree of functional independence. The most important tasks of a systematic approach include:

1) development of means for representing the studied and constructed objects as systems;

2) construction of generalized models of the system, models of different classes and specific properties of systems;

3) study of the structure of systems theories and various system concepts and developments.

In a system study, the analyzed object is considered as a certain set of elements, the interconnection of which determines the integral properties of this set. The main emphasis is on identifying the variety of connections and relationships that take place both within the object under study and in its relationship with the external environment. The properties of an object as an integral system are determined not only and not so much by summing up its properties individual elements, how many properties of its structure, special system-forming, integrative connections of the object in question. To understand the behavior of systems, primarily goal-oriented, it is necessary to identify the management processes implemented by this system - forms of information transfer from one subsystem to another and ways of influencing some parts of the system on others, coordination of the lower levels of the system by elements of its higher level, management, influence on the last of all other subsystems. Significant importance in the system approach is given to identifying the probabilistic nature of the behavior of the objects under study. An important feature of the system approach is that not only the object, but the research process itself acts as a complex system, the task of which, in particular, is to combine various object models into a single whole. Finally, system objects, as a rule, are not indifferent to the process of their study and in many cases can have a significant impact on it.

1.2 Basic principles of the systems approach

The main principles of the systems approach are:

1. Integrity, which makes it possible to consider the system at the same time as a whole and at the same time as a subsystem for higher levels. 2. Hierarchical structure, i.e. the presence of a plurality (at least two) of elements located on the basis of the subordination of elements of a lower level to elements of a higher level. The implementation of this principle is clearly visible in the example of any particular organization. As you know, any organization is an interaction of two subsystems: managing and managed. One is subordinate to the other. 3. Structurization, which allows you to analyze the elements of the system and their relationships within a specific organizational structure. As a rule, the process of functioning of the system is determined not so much by the properties of its individual elements, but by the properties of the structure itself.

4. Multiplicity, which allows using a variety of cybernetic, economic and mathematical models to describe individual elements and the system as a whole.

As noted above, with a systematic approach, it is important to study the characteristics of an organization as a system, i.e. "input", "process" characteristics and "output" characteristics.

With a systematic approach based on marketing research, the parameters of the "exit" are first investigated, i.e. goods or services, namely what to produce, with what quality indicators, at what cost, for whom, in what time frame to sell and at what price. The answers to these questions should be clear and timely. As a result, the "output" should be competitive products or services. The login parameters are then determined, i.e. the need for resources (material, financial, labor and information) is investigated, which is determined after a detailed study of the organizational and technical level of the system under consideration (the level of technology, technology, features of the organization of production, labor and management) and the parameters of the external environment (economic, geopolitical, social, environmental and etc.).

And, finally, no less important is the study of the parameters of the process that converts resources into finished products. At this stage, depending on the object of study, production technology or management technology is considered, as well as factors and ways to improve it.

Thus, a systematic approach allows us to comprehensively evaluate any production and economic activity and the activity of the management system at the level of specific characteristics. This will help to analyze any situation within a single system, to identify the nature of the input, process and output problems.

The application of a systematic approach allows the best way to organize the decision-making process at all levels in the management system. An integrated approach involves taking into account the analysis of both the internal and external environment of the organization. This means that it is necessary to take into account not only internal, but also external factors - economic, geopolitical, social, demographic, environmental, etc. Factors are important aspects in the analysis of organizations and, unfortunately, are not always taken into account. For example, often social issues are not taken into account or postponed when designing new organizations. When introducing new equipment, ergonomic indicators are not always taken into account, which leads to increased fatigue of workers and, as a result, to a decrease in labor productivity. When forming new labor collectives, socio-psychological aspects, in particular, the problems of labor motivation, are not properly taken into account. Summarizing the above, it can be argued that an integrated approach is a necessary condition for solving the problem of analyzing an organization.

The essence of the system approach was formulated by many authors. It was formulated in expanded form by V. G. Afanasyev, who defined a number of interrelated aspects that, together and unitedly, constitute a system approach: - system-elemental, answering the question of what (what components) the system is formed from;

system-structural, revealing the internal organization of the system, the way of interaction of its components;

- system-functional, showing what functions the system and its constituent components perform;

system-communication, revealing the relationship of a given system with others, both horizontally and vertically;

system-integrative, showing the mechanisms, factors of conservation, improvement and development of the system;

System-historical, answering the question of how, how the system arose, what stages it went through in its development, what are its historical prospects. The rapid growth of modern organizations and their level of complexity, the variety of operations performed have led to the fact that the rational implementation of management functions has become extremely difficult, but at the same time even more important for the success of the enterprise. To cope with the inevitable increase in the number of transactions and their complexity, a large organization must base its activities on a systematic approach. Within this approach, the leader can more effectively integrate their activities in managing the organization.

The systems approach contributes, as already mentioned, mainly to the development of the correct method of thinking about the management process. The leader must think in accordance with a systematic approach. When studying a systems approach, a way of thinking is instilled, which, on the one hand, helps to eliminate unnecessary complexity, and on the other hand, helps the manager to understand the essence of complex problems and make decisions based on a clear understanding of the environment. It is important to structure the task, to outline the boundaries of the system. But it is equally important to consider that the systems that the manager has to deal with in the course of their activities are part of larger systems, perhaps including the entire industry or several, sometimes many, companies and industries, or even the whole society as a whole. These systems are constantly changing: they are created, operate, reorganized and, sometimes, eliminated.

The system approach is the theoretical and methodological basis of system analysis.

2. Basic elements of system analysis

2. 1 Conceptual apparatus of system analysis

System analysis is a scientific method for studying complex, multi-level, multi-component systems and processes, based on an integrated approach, taking into account the relationships and interactions between the elements of the system, as well as a set of methods for developing, making and justifying decisions in the design, creation and management of social, economic, human - machine and technical systems.

The term "system analysis" first appeared in 1948 in the works of the RAND corporation in connection with the tasks of external control, and became widespread in the domestic literature after the translation of S. Optner's book. Optner S. L., System analysis for solving business and industrial problems, trans. from English, M., 1969;

System analysis is not a set of guidelines or principles for managers, it is a way of thinking in relation to organization and management. System analysis is used in cases where they seek to explore an object from different angles, in a complex manner. The most common area of systems research is considered to be system analysis, which is understood as a methodology for solving complex problems and problems based on concepts developed within the framework of systems theory. Systems analysis is also defined as "the application of systems concepts to management functions associated with planning", or even with strategic planning and target planning stage.

The involvement of system analysis methods is necessary, first of all, because in the decision-making process one has to make a choice in conditions of uncertainty, which is due to the presence of factors that cannot be rigorously quantified. The procedures and methods of system analysis are aimed precisely at putting forward alternative options for solving the problem, identifying the extent of uncertainty for each of the options and comparing the options according to certain performance criteria. System analysts only prepare or recommend solutions, while making a decision remains within the competence of the relevant official (or body).

The intensive expansion of the scope of using system analysis is closely related to the spread of the program-target method of management, in which a program is drawn up specifically for solving an important problem, an organization (an institution or a network of institutions) is formed, and the necessary material resources are allocated.

A system analysis of the activities of an enterprise or organization is carried out at the early stages of work on the creation of a specific management system.

The ultimate goal of system analysis is the development and implementation of the selected reference model of the control system.

In accordance with the main goal, it is necessary to carry out the following studies of a systemic nature:

identify general trends in the development of this enterprise and its place and role in the modern market economy;

establish the features of the functioning of the enterprise and its individual divisions;

identify the conditions that ensure the achievement of the goals;

determine the conditions that impede the achievement of goals;

collect the necessary data for analysis and development of measures to improve the current management system;

use the best practices of other enterprises;

study the necessary information to adapt the selected (synthesized) reference model to the conditions of the enterprise in question.

The following characteristics are found in the process of system analysis:

the role and place of this enterprise in the industry;

the state of production and economic activity of the enterprise;

production structure of the enterprise;

management system and its organizational structure;

features of the interaction of the enterprise with suppliers, consumers and higher organizations;

innovative needs (possible connections of this enterprise with research and design organizations;

forms and methods of stimulating and remunerating employees.

Thus, system analysis begins with the clarification or formulation of the goals of a particular management system (enterprise or company) and the search for a performance criterion that should be expressed as a specific indicator. As a rule, most organizations are multipurpose. A set of goals follows from the characteristics of the development of an enterprise (company) and its actual state in the period under consideration, as well as the state of the environment (geopolitical, economic, social factors). The primary task of system analysis is to determine global goal development of the organization and goals of functioning.

Clearly and competently formulated goals for the development of an enterprise (company) are the basis for system analysis and development of a research program.

The system analysis program, in turn, includes a list of issues to be researched and their priority:

1. Analysis of the organizational subsystem, which includes:

policy analysis (objectives);

concept analysis, i.e. systems of views, assessments, ideas for achieving the goals, methods of solution;

analysis of management methods;

analysis of methods of labor organization;

analysis of the structural-functional scheme;

analysis of the system of selection and placement of personnel;

analysis of information flows;

marketing system analysis;

analysis of the security system.

2. Analysis of the economic subsystem and diagnostics of predacceptance.

Economic diagnostics of an enterprise - analysis and evaluation of the economic performance of an enterprise based on the study of individual results, incomplete information in order to identify possible prospects for its development and the consequences of current management decisions. As a result of diagnostics, based on an assessment of the state of farms and its efficiency, conclusions are drawn that are necessary for making quick but important decisions, for example, on targeted lending, buying or selling an enterprise, closing it, etc.

Based on the analysis and research, a forecast and justification is made for changing and optimizing the existing organizational and economic subsystem of the enterprise.

2.2 Principles of system analysis

The most important principles of system analysis are as follows: the decision-making process should begin with the identification and clear formulation of ultimate goals; it is necessary to consider the whole problem as a whole, as a single system and to identify all the consequences and relationships of each particular decision; it is necessary to identify and analyze possible alternative ways to achieve the goal; the goals of individual units should not conflict with the goals of the entire program.

System analysis is based on the following principles:
1) unity - a joint consideration of the system as a single whole and as a set of parts;

2) development - taking into account the variability of the system, its ability to develop, accumulate information, taking into account the dynamics of the environment;

3) global goal - responsibility for choosing a global goal. The optimum of subsystems is not the optimum of the entire system;

4) functionality - joint consideration of the structure of the system and functions with the priority of functions over the structure;

5) decentralization - a combination of decentralization and centralization;

6) hierarchies - taking into account the subordination and ranking of parts;

7) uncertainties - taking into account the probabilistic occurrence of an event;

8) organization - the degree of implementation of decisions and conclusions.

The system analysis technique is developed and applied in those cases when decision makers do not have sufficient information about the problem situation at the initial stage, allowing them to choose the method of its formalized representation, form a mathematical model, or apply one of the new modeling approaches that combine qualitative and quantitative tricks. In such conditions, the representation of objects in the form of systems, the organization of the decision-making process using different modeling methods can help.

In order to organize such a process, it is necessary to determine the sequence of stages, recommend methods for performing these stages, and provide for a return to previous stages if necessary. Such a sequence of defined and ordered stages in a certain way with recommended methods or techniques for their implementation is a system analysis technique. The method of system analysis is developed in order to organize the decision-making process in complex problem situations. It should focus on the need to justify the completeness of the analysis, the formation of a decision-making model, and adequately reflect the process or object under consideration.

One of the fundamental features of system analysis, which distinguishes it from other areas of system research, is the development and use of tools that facilitate the formation and comparative analysis goals and functions of control systems. Initially, the methods of formation and study of goal structures were based on the collection and generalization of the experience of specialists who accumulate this experience on concrete examples. However, in this case it is impossible to take into account the completeness of the obtained data.

Thus, the main feature of the methods of system analysis is the combination of formal methods and non-formalized (expert) knowledge in them. The latter helps to find new ways to solve the problem that are not contained in the formal model, and thus continuously develop the model and the decision-making process, but at the same time be a source of contradictions, paradoxes that are sometimes difficult to resolve. Therefore, studies on system analysis are beginning to rely more and more on the methodology of applied dialectics. In view of the foregoing in the definition of systems analysis, it must be emphasized that systems analysis:

is used to solve such problems that cannot be posed and solved by separate methods of mathematics, i.e. problems with the uncertainty of the decision-making situation, when not only formal methods are used, but also methods of qualitative analysis ("formalized common sense"), intuition and experience of decision makers;

combines different methods using a single methodology; based on a scientific worldview;

unites the knowledge, judgments and intuition of specialists in various fields of knowledge and obliges them to a certain discipline of thinking;

focuses on goals and goal setting.

The characteristics of the scientific directions that have arisen between philosophy and highly specialized disciplines allow us to arrange them approximately in the following order: philosophical and methodological disciplines, systems theory, systems approach, systemology, systems analysis, systems engineering, cybernetics, operations research, special disciplines.

System analysis is located in the middle of this list, since it uses approximately equal proportions of philosophical and methodological ideas (typical for philosophy, systems theory) and formalized methods in the model (which is typical for special disciplines).

The research areas under consideration have much in common. The need for their application arises in cases where the problem (task) cannot be solved by the methods of mathematics or highly specialized disciplines. Despite the fact that initially the directions proceeded from different basic concepts (operations research - from the concept of "operation"; cybernetics - from the concepts of "control", "feedback", "system analysis", systems theory, systems engineering; systemology - from the concept of " system"), in the future, the directions operate with many identical concepts - elements, connections, goals and means, structure, etc.

Different directions also use the same mathematical methods. At the same time, there are differences between them that determine their choice in specific decision-making situations. In particular, the main specific features of system analysis that distinguish it from other system areas are:

availability, means for organizing the processes of goal formation, structuring and analysis of goals (other system areas set the task of achieving goals, developing options for achieving them and choosing the best of these options, and system analysis considers objects as systems with active elements capable of and striving for goal formation, and then to the achievement of the formed goals);

development and use of a methodology that defines the stages, sub-stages of system analysis and methods for their implementation, and the methodology combines both formal methods and models, and methods based on the intuition of specialists that help to use their knowledge, which makes system analysis particularly attractive for solving economic problems.

System analysis cannot be completely formalized, but some algorithm for its implementation can be chosen. Justification of decisions with the help of system analysis is far from always associated with the use of strict formalized methods and procedures; judgments based on personal experience and intuition are also allowed, it is only necessary that this circumstance be clearly understood.

System analysis can be performed in the following sequence:

1. Statement of the problem - the starting point of the study. In the study of a complex system, it is preceded by work on structuring the problem.

2. Expansion of the problem to a problematic, i.e. finding a system of problems that are essentially related to the problem under study, without taking into account which it cannot be solved.

3. Identification of goals: goals indicate the direction in which to move in order to solve the problem in stages.

4. Formation of criteria. The criterion is a quantitative reflection of the degree to which the system achieves its goals. A criterion is a rule for choosing a preferred solution from a number of alternative ones. There may be several criteria. Multi-criteria is a way to increase the adequacy of the goal description. Criteria should describe, as far as possible, all important aspects of the goal, but at the same time it is necessary to minimize the number of criteria required.

5. Aggregation of criteria. The identified criteria can be combined either into groups or replaced by a generalized criterion.

6. Generation of alternatives and selection using criteria of the best of them. The formation of a set of alternatives is a creative stage of system analysis.

7. Research of resource opportunities, including information resources.

8. The choice of formalization (models and constraints) to solve the problem.

9. Building a system.

10. Using the results of the conducted systematic research.

2. 3 Methods of system analysis

The central procedure in system analysis is the construction of a generalized model (or models) that reflects all the factors and relationships of the real situation that may appear in the process of implementing the decision. The resulting model is investigated in order to find out the closeness of the result of applying one or another of the alternative options for action to the desired one, the comparative cost of resources for each of the options, the degree of sensitivity of the model to various undesirable external influences. Systems analysis is based on a number of applied mathematical disciplines and methods widely used in modern management activities: operations research, method expert assessments, the critical path method, queuing theory, etc. Technical background system analysis -- modern computers and information systems.

The methodological means used in solving problems with the help of system analysis are determined depending on whether a single goal or a certain set of goals is pursued, whether one person or several people make a decision, etc. When there is one fairly clearly defined goal, the degree of achievement of which can be evaluated on the basis of one criterion, methods of mathematical programming are used. If the degree of achievement of the goal must be assessed on the basis of several criteria, the apparatus of utility theory is used, with the help of which the criteria are ordered and the importance of each of them is determined. When the development of events is determined by the interaction of several persons or systems, each of which pursues its own goals and makes its own decisions, the methods of game theory are used.

The effectiveness of the study of control systems is largely determined by the chosen and used research methods. To facilitate the choice of methods in real conditions making a decision, it is necessary to divide the methods into groups, characterize the features of these groups and give recommendations on their use in the development of models and methods of system analysis.

The whole set of research methods can be divided into three large groups: methods based on the use of knowledge and intuition of specialists; methods of formalized representation of control systems (methods of formal modeling of the processes under study) and integrated methods.

As already noted, a specific feature of system analysis is the combination of qualitative and formal methods. This combination forms the basis of any technique used. Let's consider the main methods aimed at using the intuition and experience of specialists, as well as methods of formalized representation of systems.

Methods based on the identification and generalization of the opinions of experienced experts, the use of their experience and non-traditional approaches to the analysis of the organization's activities include: the "Brainstorming" method, the "scenarios" type method, the method of expert assessments (including SWOT analysis), the " Delphi", methods such as "tree of goals", "business game", morphological methods and a number of other methods.

The above terms characterize one or another approach to enhancing the identification and generalization of the opinions of experienced experts (the term "expert" in Latin means "experienced"). Sometimes all these methods are called "expert". However, there is also a special class of methods that are directly related to the questioning of experts, the so-called method of expert assessments (since it is customary to put down marks in points and ranks in polls), therefore, these and similar approaches are sometimes combined with the term "qualitative" (specifying the convention of this name, since when processing the opinions received from specialists, quantitative methods can also be used). This term (although somewhat cumbersome) more than others reflects the essence of the methods that specialists are forced to resort to when they not only cannot immediately describe the problem under consideration by analytical dependencies, but also do not see which of the methods of formalized representation of systems considered above could help get the model.

Brainstorming methods. The concept of brainstorming has become widespread since the early 1950s as a "method of systematically training creative thinking" aimed at "discovering new ideas and reaching agreement among a group of people based on intuitive thinking."

Methods of this type pursue the main goal - the search for new ideas, their broad discussion and constructive criticism. The main hypothesis is that among a large number there are at least a few good ideas. Depending on the rules adopted and the rigidity of their implementation, there are direct brainstorming, the method of exchange of opinions, methods such as commissions, courts (when one group makes as many proposals as possible, and the second tries to criticize them as much as possible), etc. Recently, sometimes brainstorming is carried out in the form of a business game.

When conducting discussions on the issue under study, the following rules apply:

formulate the problem in basic terms, highlighting a single central point;

do not declare false And do not stop exploring any idea;

support an idea of any kind, even if its relevance seems doubtful to you at the moment;

provide support and encouragement to free the participants of the discussion from constraint.

Despite their apparent simplicity, these discussions give good results.

Scenario type methods. Methods for preparing and coordinating ideas about a problem or an analyzed object, set out in writing are called scenarios. Initially, this method involved the preparation of a text containing a logical sequence of events or possible solutions to a problem, deployed over time. However, the obligatory requirement of time coordinates was later removed, and any document containing an analysis of the problem under consideration and proposals for its solution or for the development of the system, regardless of the form in which it is presented, began to be called a scenario. As a rule, in practice, proposals for the preparation of such documents are written by experts individually at first, and then an agreed text is formed.

The scenario provides not only meaningful reasoning that helps not to miss details that cannot be taken into account in the formal model (this is actually the main role of the scenario), but also contains, as a rule, the results of a quantitative technical-economic or statistical analysis with preliminary conclusions. A group of experts preparing a scenario usually enjoys the right to obtain the necessary information from enterprises and organizations and the necessary consultations.

The role of system analysts in the preparation of the scenario is to help the leading specialists of the relevant fields of knowledge to be involved in identifying the general patterns of the system; analyze external and internal factors influencing its development and formation of goals; identify the sources of these factors; analyze the statements of leading experts in periodicals, scientific publications and other sources of scientific and technical information; create auxiliary information funds (better automated) that contribute to the solution of the corresponding problem.

Recently, the concept of a scenario has been expanding more and more in the direction of both areas of application, and presentation forms and methods for their development: quantitative parameters are introduced into the scenario and their interdependencies are established, methods for preparing a scenario using computers (computer scenarios), methods for targeted management of scenario preparation are proposed. .

The scenario allows you to create a preliminary idea of the problem (system) in situations where it is not possible to immediately display it with a formal model. But still, a script is a text with all the ensuing consequences (synonymy, homonymy, paradoxes) associated with the possibility of its ambiguous interpretation by different specialists. Therefore, such a text should be considered as the basis for developing a more formalized view of the future system or problem being solved.

Methods of expert assessments. The basis of these methods is various forms of expert survey followed by evaluation and selection of the most preferred option. The possibility of using expert assessments, the justification of their objectivity is based on the fact that an unknown characteristic of the phenomenon under study is interpreted as a random variable, the reflection of the distribution law of which is an individual assessment of the expert on the reliability and significance of an event.

It is assumed that the true value of the characteristic under study is within the range of estimates received from the group of experts and that the generalized collective opinion is reliable. The most controversial point in these methods is the establishment of weighting coefficients according to the assessments expressed by experts and the reduction of conflicting assessments to some average value.

An expert survey is not a one-time procedure. This way of obtaining information about a complex problem, characterized by a high degree of uncertainty, should become a kind of "mechanism" in a complex system, i.e. it is necessary to create a regular system of work with experts.

One of the varieties of the expert method is the method of studying the strengths and weaknesses of the organization, the opportunities and threats to its activities - the method of SWOT analysis.

This group of methods is widely used in socio-economic research.

Delphi type methods. Initially, the Delphi method was proposed as one of the brainstorming procedures and should help reduce the influence of psychological factors and increase the objectivity of expert assessments. Then the method began to be used independently. It is based on feedback, familiarizing the experts with the results of the previous round and taking these results into account when assessing the significance of the experts.

In specific methods that implement the "Delphi" procedure, this tool is used to varying degrees. So, in a simplified form, a sequence of iterative brainstorming cycles is organized. In a more complex version, a program of sequential individual surveys is developed using questionnaires that exclude contacts between experts, but provide for their acquaintance with each other's opinions between rounds. Questionnaires from tour to tour can be updated. To reduce factors such as suggestion or accommodation to the opinion of the majority, sometimes it is required that experts substantiate their point of view, but this does not always lead to the desired result, but, on the contrary, may increase the effect of adjustment. In the most advanced methods, experts are assigned weight coefficients of the significance of their opinions, calculated on the basis of previous surveys, refined from round to round, and taken into account when obtaining generalized assessment results.

Methods of the "tree of goals" type. The term "tree" implies the use of a hierarchical structure obtained by dividing the general goal into subgoals, and these, in turn, into more detailed components, which can be called subgoals of lower levels or, starting from a certain level, functions.

The goal tree method is focused on obtaining a relatively stable structure of problems, directions, i.e. goals. a structure that has changed little over a period of time with the inevitable changes that occur in any developing system.

To achieve this, when constructing the initial version of the structure, one should take into account the patterns of goal formation and use the principles of forming hierarchical structures.

Morphological methods. The main idea of the morphological approach is to systematically find all possible solutions to the problem by combining the selected elements or their features. In a systematic form, the method of morphological analysis was first proposed by the Swiss astronomer F. Zwicky and is often called the "Zwicky method".

The starting points of morphological research F. Zwicky considers:

1) equal interest in all objects of morphological modeling;

2) the elimination of all restrictions and estimates until the complete structure of the study area is obtained;

3) the most accurate formulation of the problem.

There are three main schemes of the method:

method of systematic coverage of the field, based on the allocation of the so-called strong points of knowledge in the area under study and the use of certain formulated principles of thinking to fill the field;

the method of negation and construction, which consists in formulating some assumptions and replacing them with opposite ones, followed by an analysis of the inconsistencies that arise;

morphological box method, which consists in determining all possible parameters on which the solution of the problem may depend. The identified parameters form matrices containing all possible combinations of parameters, one from each row, followed by the selection of the best combination.

business games- the simulation method has been developed for making managerial decisions in various situations by playing a group of people or a person and a computer according to the given rules. Business games allow, with the help of modeling and imitation of processes, to analyze, solve complex practical problems, ensure the formation of a thinking culture, management, communication skills, decision-making, instrumental expansion of managerial skills.

Business games act as a means of analyzing management systems and training specialists.

To describe management systems in practice, a number of formalized methods are used, which to varying degrees provide the study of the functioning of systems in time, the study of management schemes, the composition of units, their subordination, etc., in order to create normal working conditions for the management apparatus, personalization and clear information management

One of the most complete classifications based on a formalized representation of systems, i.e. on a mathematical basis, includes the following methods:

- analytical (methods of both classical mathematics and mathematical programming);

- statistical (mathematical statistics, probability theory, queuing theory);

- set-theoretic, logical, linguistic, semiotic (considered as sections of discrete mathematics);

graphic (graph theory, etc.).

The class of poorly organized systems corresponds in this classification to statistical representations. For the class of self-organizing systems, the most suitable models are discrete mathematics and graphical models, as well as their combinations.

Applied classifications are focused on economic and mathematical methods and models and are mainly determined by the functional set of tasks solved by the system.

Conclusion

Despite the fact that the range of modeling and problem solving methods used in system analysis is constantly expanding, system analysis is not identical in nature to scientific research: it is not related to the tasks of obtaining scientific knowledge in the proper sense, but is only the application of scientific methods to solving practical problems. management problems and aims to rationalize the decision-making process, without excluding inevitable subjective moments from this process.

Due to the extremely large number of components (elements, subsystems, blocks, connections, etc.) that make up socio-economic, human-machine, etc. systems, system analysis requires the use of modern computer technology - both for building generalized models of such systems, and for operating with them (for example, by playing scenarios of the functioning of systems on such models and interpreting the results obtained).

When conducting a system analysis, the team of performers becomes important. The system analysis team should include:

* Specialists in the field of system analysis -- group leaders and future project managers;

* engineers for the organization of production;

* economists specializing in the field of economic analysis, as well as researchers of organizational structures and workflow;

* specialists in the use of technical means and computer equipment;

* psychologists and sociologists.

An important feature of system analysis is the unity of the formalized and non-formalized means and methods of research used in it.

System analysis is widely used in marketing research, since it allows us to consider any market situation as an object for study with a wide range of internal and external cause-and-effect relationships.

Literature

Golubkov Z.P. The use of system analysis in decision making - M .: Economics, 1982

Ignatieva A. V., Maksimtsov M. M. RESEARCH OF CONTROL SYSTEMS, M.: UNITY-DANA, 2000

Kuzmin V.P. Historical background and epistemological foundations
systemic approach. - Psychol. journal, 1982, vol. 3, no. 3, p. 3 - 14; No. 4, p. 3 - 13.

Remennikov V.B. Development of a management solution. Proc. allowance. -- M.: UNITI-DANA, 2000.

Dictionary-reference manager./Ed. M.G. Lapusty. -- M.: INFRA, 1996.

Directory of the director of the enterprise. / Ed. M.G. La empty. -- M.: INFRA, 1998.

Smolkin A.M. Management: foundations of the organization. -- M.: INFRA-M, 1999.

8. Management of the organization. / Ed. A.G. Porshneva, Z.P. Rumyantseva, N.A. Salomatina. --M.: INFRA-M, 1999.

Lecture 1: System Analysis as a Problem Solving Methodology

It is necessary to be able to think abstractly in order to perceive the world around us in a new way.

R. Feynman

One of the areas of restructuring in higher education is to overcome the shortcomings of narrow specialization, strengthen interdisciplinary ties, develop a dialectical vision of the world, and systemic thinking. The curriculum of many universities has already introduced general and special courses that implement this trend: for engineering specialties - "design methods", "systems engineering"; for military and economic specialties - "operations research"; in administrative and political management - "political science", "futurology"; in applied scientific research - "imitation modeling", "experimental methodology", etc. Among these disciplines is the course of systems analysis, which is a typically interdisciplinary and supradisciplinary course that generalizes the methodology for studying complex technical, natural, and social systems.

1.1 System analysis in the structure of modern systems research

Currently, there are 2 opposite trends in the development of sciences:

Differentiation, when, with an increase in knowledge and the emergence of new problems, particular sciences stand out from more general sciences.
2. Integration, when more general sciences arise as a result of the generalization and development of certain sections of related sciences and their methods.

The processes of differentiation and integration are based on 2 fundamental principles of materialistic dialectics:

the principle of qualitative originality of various forms of motion of matter, def. the need to study certain aspects of the material world;
the principle of the material unity of the world, def. the need to get a holistic view of any objects of the material world.

As a result of the manifestation of the integrative trend, a new area of scientific activity has appeared: systemic research, which is aimed at solving complex large-scale problems of great complexity.

Within the framework of system research, such integration sciences as cybernetics, operations research, systems engineering, systems analysis, artificial intelligence, and others are being developed. Those. we are talking about the creation of a 5th generation computer (to remove all intermediaries between the computer and the machine. The user is unskilled.), An intelligent interface is used.

System analysis develops a system methodology for solving complex applied problems, based on the principles of a systems approach and general systems theory, development and methodologically generalizing the conceptual (ideological) and mathematical apparatus of cybernetics, operations research and systems engineering.

System analysis is a new scientific direction of the integration type, which develops a system methodology for making decisions and occupies a certain place in the structure of modern system research.

Fig.1.1 - System analysis

systems research
systems approach
specific system concepts
general systems theory (metatheory in relation to specific systems)
dialectical materialism (philosophical problems of system research)
scientific system theories and models (the doctrine of the earth's biosphere; probability theory; cybernetics, etc.)
technical systems theories and developments - operations research; systems engineering, system analysis, etc.
private theories of the system.

1.2 Classification of problems according to the degree of their structuring

According to the classification proposed by Simon and Newell, the whole set of problems, depending on the depth of their knowledge, is divided into 3 classes:

well-structured or quantified problems that lend themselves to mathematical formalization and are solved using formal methods;
unstructured or qualitatively expressed problems that are described only at a substantive level and are solved using informal procedures;
semi-structured (mixed problems), which contain quantitative and qualitative problems, and the qualitative, little-known and uncertain sides of the problems tend to dominate.

These problems are solved on the basis of the complex use of formal methods and informal procedures. The classification is based on the degree of structuring of problems, and the structure of the entire problem is determined by 5 logical elements:

a goal or set of goals;
alternatives for achieving goals;
resources spent on the implementation of alternatives;
model or series of models;
5.criteria for choosing the preferred alternative.

The degree of structuring of the problem is determined by how well the indicated elements of the problems are identified and understood.

It is characteristic that the same problem can occupy a different place in the classification table. In the process of ever deeper study, reflection and analysis, the problem can turn from unstructured to semi-structured, and then from semi-structured to structured. In this case, the choice of a method for solving a problem is determined by its place in the classification table.

Fig.1.2 - Table of classifications

identification of the problem;
formulation of the problem;
solution to the problem;
unstructured problem (can be solved using heuristic methods);
methods of expert assessments;
poorly structured problem;
methods of system analysis;
well structured problem;
operations research methods;
decision-making;
solution implementation;
solution evaluation.

1.3 Principles for solving well-structured problems

To solve problems of this class, the mathematical methods of I.O. In operational research, the main stages can be distinguished:

Identification of competing strategies to achieve the goal.
Construction of a mathematical model of the operation.
Evaluation of the effectiveness of competing strategies.
Choosing the optimal strategy for achieving goals.

The mathematical model of the operation is a functional:

E = f(x∈x → , (α), (β)) ⇒ extz

E is a criterion for the effectiveness of operations;
x is the strategy of the operating party;
α is the set of conditions for conducting operations;
β is the set of environmental conditions.

The model allows evaluating the effectiveness of competing strategies and choosing the optimal strategy from among them.

persistence of the problem
restrictions
operation efficiency criterion
mathematical model of the operation
model parameters, but some of the parameters are usually unknown, so (6)
predicting information (i.e. you need to predict a number of parameters)
competing strategies
analysis and strategies
optimal strategy
approved strategy (simpler, but which satisfies a number of other criteria)
solution implementation
model adjustment

The criterion for the effectiveness of the operation must satisfy a number of requirements:

Representativeness, i.e. the criterion should reflect the main, and not the secondary, purpose of the operation.
Criticality - i.e. the criterion must change when changing the operation parameters.
Uniqueness, since only in this case it is possible to find a rigorous mathematical solution to the optimization problem.
Accounting for stochasticity, which is usually associated with the random nature of some parameters of operations.
Accounting for uncertainties, which is associated with the lack of any information about some parameters of operations.
Accounting for the counteraction that is often caused by a conscious adversary who controls the overall parameters of operations.
Simple, because a simple criterion allows you to simplify the mathematical calculations when searching for opt. solutions.

Here is a diagram that illustrates the basic requirements for the criterion of the effectiveness of operations research.

Rice. 1.4 - A diagram that illustrates the requirements for the performance criterion of operations research

statement of the problem (2 and 4 (restrictions) follow);
efficiency criterion;
top level tasks
restrictions (we organize the nesting of models);
communication with top-level models;
representativeness;
criticality;
uniqueness;
accounting for stochasticity;
accounting for uncertainty;
accounting for counteraction (game theory);
simplicity;
mandatory restrictions;
additional restrictions;
artificial restrictions;
choice of the main criterion;
translation of restrictions;
building a generalized criterion;
assessment of mathematical otid-I;
construction of confidence intervals:
analysis of possible options (there is a system; we do not know exactly what the intensity of the input flow is; we can only assume one or another intensity with a certain probability; then we weigh the output options).

Uniqueness - so that the problem can be solved by strictly mathematical methods.

Points 16, 17 and 18 are ways that allow you to get rid of multi-criteria.

Accounting for stochasticity - most of the parameters have a stochastic value. In some cases, stoch. we set in the form of a f-and distribution, therefore, the criterion itself must be averaged, i.e. apply mathematical expectations, therefore, items 19, 20, 21.

1.4 Principles for solving unstructured problems

To solve problems of this class, it is advisable to use methods of expert assessments.

Methods of expert assessments are used in cases where the mathematical formalization of problems is either impossible due to their novelty and complexity, or requires a lot of time and money. Common to all methods of expert assessments is the appeal to the experience, guidance and intuition of specialists performing the functions of experts. Giving answers to the question, the experts are, as it were, sensors of information that is analyzed and generalized. It can be argued, therefore: if there is a true answer in the range of answers, then the set of disparate opinions can be effectively synthesized into some generalized opinion close to reality. Any method of expert assessments is a set of procedures aimed at obtaining information of heuristic origin and processing this information using mathematical and statistical methods.

The process of preparing and conducting an examination includes the following steps:

definition of chains of expertise;
formation of a group of analysts;
formation of a group of experts;
development of the scenario and examination procedures;
collection and analysis of expert information;
processing of expert information;
analysis of the results of the examination and decision-making.

When forming a group of experts, it is necessary to take into account their individual x-ki, which affect the results of the examination:

competence (professional level)
creativity ( Creative skills person)
constructive thinking (do not "fly" in the clouds)
conformism (susceptibility to the influence of authority)
relation to expertise
collectivism and self-criticism

Methods of expert assessments are applied quite successfully in the following situations:

choice of goals and topics of scientific research
selection of options for complex technical and socio-economic projects and programs
construction and analysis of models of complex objects
construction of criteria in vector optimization problems
classification of homogeneous objects according to the degree of manifestation of a property
assessment of product quality and new technology
decision making in production management tasks
long-term and current production planning, research and development
scientific, technical and economic forecasting, etc. etc.

1.5 Principles for solving semi-structured problems

To solve problems of this class, it is advisable to use the methods of system analysis. Problems solved with the help of system analysis have a number of characteristic features:

the decision being made is for the future (plant that does not yet exist)
there is a wide range of alternatives
solutions depend on the current incompleteness of technological advances
decisions taken require large investments of resources and contain elements of risk
requirements related to the cost and time of solving the problem are not fully defined
the internal problem is complex due to the fact that its solution requires a combination of various resources.

The main concepts of systems analysis are as follows:

the process of solving a problem should begin with the identification and justification of the ultimate goal that they want to achieve in a particular area, and already on this basis intermediate goals and objectives are determined
any problem must be approached as a complex system, while identifying all possible details and relationships, as well as the consequences of certain decisions
in the process of solving the problem, the formation of many alternatives to achieve the goal is carried out; evaluation of these alternatives using appropriate criteria and selection of the preferred alternative
the organizational structure of a problem-solving mechanism should be subordinated to a goal or set of goals, and not vice versa.

System analysis is a multi-step iterative process, and the starting point of this process is the formulation of the problem in some initial form. When formulating the problem, it is necessary to take into account 2 conflicting requirements:

the problem should be formulated broadly enough so as not to miss anything essential;
the problem must be formed in such a way that it is visible and can be structured. In the course of system analysis, the degree of structuring of the problem increases, i.e. the problem is being formulated more and more clearly and comprehensively.

Rice. 1.5 - One step system analysis

formulation of the problem
goal rationale
formation of alternatives
resource research
model building
evaluation of alternatives
decision making (choosing one decision)
sensitivity analysis
verification of initial data
clarification of the final goal
search for new alternatives
analysis of resources and criteria

1.6 Main steps and methods of SA

SA provides for: the development of a systematic method for solving the problem, i.e. a logically and procedurally organized sequence of operations aimed at choosing the preferred solution alternative. SA is being implemented practically in several stages, however, there is still no unity regarding their number and content, because A wide variety of applied problems.

Here is a table that illustrates the main regularities of SA 3 different scientific schools.

The main stages of system analysis
According to F. Hansman Germany, 1978	According to D. Jeffers USA, 1981	According to V. V. Druzhinin USSR, 1988
General orientation in the problem (sketch statement of the problem) Selection of appropriate criteria Formation of alternative solutions Identification of significant environmental factors Model building and validation Estimation and prediction of model parameters Getting information based on the model Preparing to choose a solution Implementation and control	Problem selection Statement of the problem and limitation of the degree of its complexity Establishing a hierarchy, goals and objectives The choice of ways to solve the problem Modeling Evaluation of possible strategies Implementation of results	Highlighting a problem Description Establishing criteria Idealization (limiting simplification, an attempt to build a model) Decomposition (breaking down into parts, finding solutions in parts) Composition ("gluing" parts together) Making the Best Decision

The scientific tools of SA include the following methods:

scripting method (trying to describe the system)
goal tree method (there is an ultimate goal, it is divided into subgoals, subgoals into problems, etc., i.e. decomposition to tasks that we can solve)
morphological analysis method (for inventions)
expert assessment methods
probabilistic-statistical methods (theory of MO, games, etc.)
cybernetic methods (object in the form of a black box)
IO methods (scalar opt)
vector optimization methods
simulation methods (e.g. GPSS)
network methods
matrix methods
methods of economic analysis, etc.

In the SA process, at its different levels, various methods in which heuristics is combined with formalism. SA acts as a methodological framework that combines all the necessary methods, research techniques, activities and resources for problem solving.

1.7 The decision maker's preference system and a systematic approach to the decision-making process.

The decision-making process consists in choosing a rational decision from a certain set of alternative decisions, taking into account the decision maker's preference system. Like any process in which a person participates, it has 2 sides: objective and subjective.

The objective side is what is real outside of human consciousness, and the subjective side is what is reflected in the human consciousness, i.e. objective in the human mind. The objective is not always adequately reflected in the mind of a person, but it does not follow from this that it cannot be right decisions. Practically correct is such a decision, which in the main features correctly reflects the situation and corresponds to the task.

The decision maker's preference system is determined by many factors:

understanding of the problem and development prospects;
current information about the state of some operation and the external conditions of its flow;
directives from higher authorities and various kinds of restrictions;
legal, economic, social, psychological factors, traditions, etc.

Rice. 1.6 - Decision maker preference system

directives from higher authorities on the goals and objectives of operations (technical processes, forecasting)
restrictions on resources, degree of independence, etc.
information processing
operation
external conditions (external environment), a) determination; b) stochastic (the computer fails after a random interval t); c) organized resistance
information about external conditions
rational solution
control synthesis (system dependent)

Being in this vice, the decision maker must normalize the set of potentially possible solutions of them. From them, select 4-5 best ones and from them - 1 solution.

A systematic approach to the decision-making process consists in the implementation of 3 interrelated procedures:

There are many potential solutions.
A set of competing solutions is selected from among them.
A rational solution is chosen taking into account the decision maker's preference system.

Rice. 1.7 - A systematic approach to the decision-making process

possible solutions
competing solutions
rational solution
purpose and objectives of the operation
operation status information
information about external conditions
1. stochastic
2. organized opposition
resource limit
limitation on the degree of autonomy
additional restrictions and conditions
1. legal factors
2. economic forces
3. sociological factors
4. psychological factors
5. traditions and more
efficiency criterion

Modern systems analysis is an applied science aimed at finding out the causes of real difficulties that arose before the "owner of the problem" and at developing options for eliminating them. In its most advanced form, systems analysis also includes direct, practical, improving intervention in a problem situation.

Consistency should not seem like some kind of innovation, the latest achievement of science. Consistency is a universal property of matter, a form of its existence, and hence an integral property of human practice, including thinking. Any activity can be less or more systemic. The appearance of a problem is a sign of insufficient consistency; problem solving is the result of increasing systemicity. Theoretical thought at different levels of abstraction reflected the systemic nature of the world in general and the systemic nature of human knowledge and practice. At the philosophical level, this is dialectical materialism; at the general scientific level, it is systemology and general systems theory, organization theory; in the natural sciences - cybernetics. With the development of computer technology, computer science and artificial intelligence arose.

In the early 1980s, it became obvious that all these theoretical and applied disciplines form, as it were, a single stream, a “systemic movement”. Consistency becomes not only a theoretical category, but also a conscious aspect of practical activity. Since large and complex systems necessarily became the subject of study, control and design, it was necessary to generalize the methods of studying systems and methods of influencing them. Some kind of applied science should have arisen, which is a “bridge” between abstract theories of systemicity and living systemic practice. It arose - at first, as we noted, in various fields and under different names, and in recent years it has formed into a science that has been called "system analysis".

The features of modern systems analysis stem from the very nature of complex systems. Having as a goal the elimination of the problem or, at least, the clarification of its causes, system analysis involves a wide range of means for this, uses the possibilities of various sciences and practical fields of activity. Being essentially an applied dialectic, system analysis attaches great importance to the methodological aspects of any system research. On the other hand, the applied orientation of system analysis leads to the use of all modern means of scientific research - mathematics, computer technology, modeling, field observations and experiments.

During the study of a real system, one usually has to deal with a wide variety of problems; it is impossible for one person to be a professional in each of them. The way out seems to be that whoever undertakes to carry out a systems analysis has the education and experience necessary to identify and classify specific problems, to determine which specialists should be contacted to continue the analysis. This imposes special requirements on system specialists: they must have broad erudition, relaxed thinking, the ability to attract people to work, and organize collective activities.

After listening to this course of lectures, or reading several books on the subject, one cannot become a specialist in systems analysis. As W. Shakespeare put it: “If doing would be as easy as knowing what to do, chapels would be cathedrals, huts would be palaces.” Professionalism is acquired in practice.

Let's consider a curious forecast of the most rapidly expanding areas of employment in the US: Dynamics in % 1990-2000.

nursing staff - 70%
radiation technology specialists - 66%
travel agency agents - 54%
computer systems analysts - 53%
programmers - 48%
electronic engineers - 40%

Development of system views

What does the word "system" or "large system" itself mean, what does it mean to "act systematically"? We will receive answers to these questions gradually, increasing the level of the systemic nature of our knowledge, which is the goal of this course of lectures. In the meantime, we have enough of those associations that arise when the word “system” is used in ordinary speech in combination with the words “socio-political”, “Solar”, “nervous”, “heating” or “equations”, “indicators”, “views and beliefs." Subsequently, we will consider in detail and comprehensively the signs of systemicity, and now we will note only the most obvious and mandatory of them:

structured system;
interconnectedness of its constituent parts;
the subordination of the organization of the entire system to a specific goal.

Systematic practice

In relation, for example, to human activity, these signs are obvious, since each of us can easily detect them in his own practical activity. All our conscious action pursues a well-defined goal; in any action it is easy to see its component parts, smaller actions. In this case, the components are performed not in an arbitrary order, but in a certain sequence. This is a certain interconnectedness of the constituent parts, subordinate to the goal, which is a sign of systemicity.

Systematic and algorithmic

Another name for such a construction of activity is algorithmicity. The concept of an algorithm arose first in mathematics and meant the task of a precisely defined sequence of unambiguously understood operations on numbers or other mathematical objects. In recent years, the algorithmic nature of any activity has begun to be realized. They are already talking not only about algorithms for making managerial decisions, about learning algorithms, algorithms for playing chess, but also about algorithms for invention, algorithms for composing music. We emphasize that in this case a departure from the mathematical understanding of the algorithm is made: while maintaining the logical sequence of actions, it is assumed that the algorithm may contain non-formalized actions. Thus, the explicit algorithmization of any practical activity is an important feature of its development.

Systematic cognitive activity

One of the features of cognition is the presence of analytical and synthetic ways of thinking. The essence of analysis is to divide the whole into parts, to represent the complex as a set of simpler components. But in order to cognize the whole, the complex, the reverse process is also necessary - synthesis. This applies not only to individual thinking, but also to universal human knowledge. Let's just say that the division of thinking into analysis and synthesis and the interconnectedness of these parts are the most important sign of the systematic nature of knowledge.

Consistency as a universal property of matter

Here it is important for us to highlight the idea that systemicity is not only a property of human practice, including both external active activity and thinking, but a property of all matter. The systemic nature of our thinking follows from the systemic nature of the world. Modern scientific data and modern system concepts allow us to speak of the world as an infinite hierarchical system of systems that are in development and at different stages of development, at different levels of the system hierarchy.

Summarize

In conclusion, as information for reflection, we present a diagram depicting the relationship of the issues discussed above.

Fig 1.8 - Relationship of the issues discussed above

Methods of system analysis

System analysis- a scientific method of cognition, which is a sequence of actions to establish structural relationships between variables or elements of the system under study. It is based on a set of general scientific, experimental, natural science, statistical, and mathematical methods.

To solve well-structured quantifiable problems, the well-known methodology of operations research is used, which consists in constructing an adequate mathematical model (for example, linear, nonlinear, dynamic programming problems, problems of queuing theory, game theory, etc.) and applying methods to find the optimal control strategy targeted actions.

System analysis provides the following system methods and procedures for use in various sciences, systems:

abstraction and specification

analysis and synthesis, induction and deduction

Formalization and concretization

composition and decomposition

Linearization and selection of non-linear components

Structuring and restructuring

· prototyping

reengineering

algorithmization

simulation and experiment

software control and regulation

Recognition and identification

clustering and classification

expert evaluation and testing

verification

and other methods and procedures.

It should be noted the tasks of studying the system of interactions of the analyzed objects with the environment. The solution to this problem involves:

- drawing a boundary between the system under study and the environment, which determines the maximum depth

the influence of the interactions under consideration, to which the consideration is limited;

- determination of the real resources of such interaction;

– consideration of the interactions of the system under study with a higher level system.

Tasks of the following type are associated with the design of alternatives for this interaction, alternatives for the development of the system in time and space. An important direction in the development of systems analysis methods is associated with attempts to create new possibilities for constructing original solution alternatives, unexpected strategies, unusual ideas and hidden structures. In other words, speech here about the development of methods and means strengthening the inductive possibilities of human thinking, in contrast to its deductive possibilities, to which, in fact, the development of formal logical means is aimed at strengthening. Research in this direction has begun only quite recently, and there is still no single conceptual apparatus in them. Nevertheless, several important areas can be distinguished here, such as the development the formal apparatus of inductive logic, methods of morphological analysis and other structural and syntactic methods for constructing new alternatives, syntactic methods and organization of group interaction in solving creative problems, as well as the study of the main paradigms of search thinking.

Tasks of the third type consist in constructing a set simulation models describing the influence of one or another interaction on the behavior of the object of study. It should be noted that system studies do not pursue the goal of creating some kind of supermodel. We are talking about the development of private models, each of which solves its own specific issues.

Tasks of the fourth type are associated with the design decision making models. Any system study is connected with the study of various alternatives for the development of the system. The task of system analysts is to choose and justify the best development alternative. At the stage of development and decision-making, it is necessary to take into account the interaction of the system with its subsystems, combine the goals of the system with the goals of the subsystems, and single out global and secondary goals.

a) building a theory for evaluating the effectiveness of decisions made or plans and programs formed;

b) solving the problem of multi-criteria in the evaluation of decision or planning alternatives;

d) development of the problem of aggregating individual preferences on decisions affecting the interests of several parties that affect the behavior of the system;

e) study of specific features of socio-economic criteria of efficiency;

information about both external events and changes in ideas about the execution of this program.

The latter direction requires a new awareness of the real functions of the target structures, plans, programs and the definition of those that they should perform, as well as the links between them.

ANALYTICAL AND STATISTICAL METHODS. These groups of methods are most widely used in the practice of design and management. True, graphical representations (graphs, diagrams, etc.) are widely used to present intermediate and final results of modeling. However, the latter are auxiliary; the basis of the model, the proofs of its adequacy, are those or other directions of analytical and statistical representations. Therefore, despite the fact that in the main areas of these two classes of methods, universities read independent courses lectures, we nevertheless briefly characterize their features, advantages and disadvantages from the point of view of the possibility of using them in system modeling.

Analytical in the classification under consideration, methods are named that display real objects and processes in the form of points (dimensionless in strict mathematical proofs) that make any movements in space or interact with each other. The basis of the conceptual (terminological) apparatus of these representations is the concepts of classical mathematics (value, formula, function, equation, system of equations, logarithm, differential, integral, etc.).

Analytical representations have a long history of development, and they are characterized not only by the desire for rigor of terminology, but also by assigning certain letters to some special quantities (for example, doubling the ratio of the area of a circle to the area of a square inscribed in it p» 3.14; the base of the natural logarithm – e» 2.7, etc.).

On the basis of analytical concepts, mathematical theories of varying complexity have arisen and are developing - from the apparatus of the classical mathematical analysis(methods for studying functions, their form, methods of representation, searching for extrema of functions, etc.) to such new sections of modern mathematics as mathematical programming (linear, nonlinear, dynamic, etc.), game theory (matrix games with pure strategies, differential games, etc.).

These theoretical directions have become the basis of many applied ones, including the theory of automatic control, the theory of optimal solutions, etc.

When modeling systems, a wide range of symbolic representations is used, using the "language" of classical mathematics. However, these symbolic representations do not always adequately reflect real complex processes, and in these cases, generally speaking, they cannot be considered rigorous mathematical models.

Most of the areas of mathematics do not contain the means of setting the problem and proving the adequacy of the model. The latter is proved by experiment, which, as the problems become more complex, also becomes more and more complex, expensive, not always indisputable and realizable.

At the same time, this class of methods includes a relatively new area of mathematics - mathematical programming, which contains the means of setting the problem and expands the possibilities of proving the adequacy of models.

Statistical ideas were formed as an independent scientific direction in the middle of the last century (although they arose much earlier). They are based on the display of phenomena and processes using random (stochastic) events and their behavior, which are described by the corresponding probabilistic (statistical) characteristics and statistical patterns. Statistical mappings of the system in the general case (by analogy with analytical ones) can be represented as if in the form of a “blurred” point (fuzzy area) in n-dimensional space, into which the system (its properties taken into account in the model) is transferred by the operator F. “Blurred” point should be understood as a certain area characterizing the movement of the system (its behavior); in this case, the boundaries of the region are given with a certain probability p (“blurred”) and the movement of the point is described by some random function.

Fixing all the parameters of this area, except for one, you can get a cut along the line a - b, the meaning of which is the impact of this parameter on the behavior of the system, which can be described by a statistical distribution for this parameter. Similarly, you can get two-dimensional, three-dimensional, etc. statistical distribution patterns. Statistical regularities can be represented as discrete random variables and their probabilities, or as continuous dependences of the distribution of events and processes.

For discrete events, the relation between possible values random variable xi and their probabilities pi, is called the distribution law.

Brainstorming method

A group of researchers (experts) develops ways to solve the problem, while any method (any thought expressed aloud) is included in the number of considerations than more ideas- all the better. At the preliminary stage, the quality of the proposed methods is not taken into account, that is, the subject of the search is the creation of a possible more problem solving options. But to be successful, the following conditions must be met:

the presence of an inspirer of ideas;

· a group of experts does not exceed 5-6 people;

· the potential of researchers is commensurable;

the environment is calm;

equal rights are observed, any solution can be proposed, criticism of ideas is not allowed;

· Duration of work no more than 1 hour.

After the "flow of ideas" stops, the experts carry out a critical selection of proposals, taking into account the limitations of the organizational and economic nature. Selection best idea can be based on several criteria.

This method is most productive at the stage of developing a solution for the implementation of the goal, when revealing the mechanism of the system's functioning, when choosing a criterion for solving the problem.

The method of "concentration of attention on the goals of the problem"

This method consists in selecting one of the objects (elements, concepts) associated with the problem being solved. At the same time, it is known that the object accepted for consideration is directly related to the ultimate goals of this problem. Then the connection between this object and some other, chosen at random, is examined. Next, the third element is selected, just as randomly, and its relationship with the first two is examined, and so on. Thus, a certain chain of interconnected objects, elements or concepts is created. If the chain breaks, then the process resumes, a second chain is created, and so on. This is how the system is explored.

Method "inputs-outputs of the system"

The system under study is necessarily considered together with the environment. Wherein Special attention refers to the restrictions that the external environment imposes on the system, as well as the restrictions inherent in the system itself.

At the first stage of studying the system, possible outputs of the system are considered and the results of its functioning are evaluated according to changes in the environment. Then the possible inputs of the system and their parameters are investigated, which allow the system to function within the limits of the accepted restrictions. And, finally, at the third stage, acceptable inputs are chosen that do not violate the system's limitations and do not bring it into conflict with the goals of the environment.

This method is most effective at the stages of understanding the mechanism of the system functioning and decision making.

Scenario method

The peculiarity of the method is that a group of highly qualified specialists in a descriptive form represents the possible course of events in a particular system - starting from the current situation and ending with some resulting situation. At the same time, artificially erected, but arising in real life, restrictions on the input and output of the system (on raw materials, energy resources, finance, and so on) are observed.

The main idea of this method is to identify the connections of various elements of the system that manifest themselves in a particular event or constraint. The result of such a study is a set of scenarios - possible directions for solving the problem, from which, by comparing according to some criterion, the most acceptable ones could be chosen.

Morphological method

This method involves the search for all possible solutions to the problem by exhaustive census of these solutions. For example, F.R. Matveev identifies six stages in the implementation of this method:

the formulation and definition of the constraints of the problem;

search for possible decision parameters and possible variations of these parameters;

Finding all possible combinations of these parameters in the resulting solutions;

Comparison of decisions in terms of the goals pursued;

Choice of solutions

· in-depth study of selected solutions.

Modeling methods

A model is a system created to represent a complex reality in a simplified and understandable form, in other words, a model is an imitation of this reality.

The problems solved by models are many and varied. The most important of them:

· with the help of models, researchers try to better understand the course of a complex process;

· with the help of models, experimentation is carried out in the case when this is not possible on a real object;

· with the help of models, the possibility of implementing various alternative solutions is evaluated.

In addition, the models have valuable properties how:

reproducibility by independent experimenters;

· variability and the possibility of improvement by introducing new data into the model or modifying relationships within the model.

Among the main types of models, symbolic and mathematical models should be noted.

Symbolic models - diagrams, diagrams, graphs, flowcharts and so on.

Mathematical models are abstract constructions that describe in mathematical form the connections, relationships between the elements of the system.

When building models, the following conditions must be observed:

have a sufficiently large amount of information about the behavior of the system;

Stylization of the functioning mechanisms of the system should take place within such limits that it would be possible to accurately reflect the number and nature of the relationships and connections existing in the system;

The use of automatic information processing methods, especially when the amount of data is large or the nature of the relationship between the elements of the system is very complex.

However, mathematical models have some disadvantages:

the desire to reflect the process under study in the form of conditions leads to a model that can be understood only by its developer;

On the other hand, simplification leads to a limitation of the number of factors included in the model; consequently, there is an inaccuracy in the reflection of reality;

· the author, having created a model, "forgets" that he does not take into account the action of numerous, maybe insignificant factors. But the combined effect of these factors on the system is such that the final results cannot be achieved on this model.

In order to level these shortcomings, the model must be checked:

How realistically and satisfactorily does it reflect the real process?

· whether changing the parameters causes a corresponding change in the results.

Complex systems, due to the presence of many discretely functioning subsystems, as a rule, cannot be adequately described using only mathematical models, so simulation modeling has become widespread. Simulation models have become widespread for two reasons: firstly, these models allow the use of all available information (graphic, verbal, mathematical models ...) and, secondly, because these models do not impose strict restrictions on the input data used. Thus, simulation models allow you to creatively use all the available information about the object of study.

home > healthcare

“System Analysis and Design. Classification of problems according to the degree of their structuring

Send your good work in the knowledge base is simple. Use the form below

Similar Documents

Send your good work in the knowledge base is simple. Use the form below

Similar Documents

Send your good work in the knowledge base is simple. Use the form below

1 Content and characteristics of a systematic approach

"System" is a Greek word (systema), literally meaning a whole made up of parts; a set of elements that are in relationships and connections with each other and form a certain integrity, unity.

Other words can be formed from the word "system": "systemic", "systematize", "systematic". In a narrow sense, we understand the system approach as the application of system methods to study real physical, biological, social, and other systems.

The systems approach in a broad sense includes, in addition, the application of system methods for solving the problems of systematics, planning and organizing a complex and systematic experiment.

The term "system approach" covers a group of methods by which a real object is described as a set of interacting components. These methods are developed within the framework of individual scientific disciplines, interdisciplinary syntheses and general scientific concepts.

In the process of synthesis, a model of a real system is created, the level of an abstract description of the system rises, the completeness of its composition and structures, the bases of the description, the laws of dynamics and behavior are determined.

The system approach is applied to sets of objects, individual objects and their components, as well as to the properties and integral characteristics of objects.

It is necessary to define the scope of these concepts.

1) development of means for representing the studied and constructed objects as systems;

2) construction of generalized models of the system, models of different classes and specific properties of systems;

3) study of the structure of systems theories and various system concepts and developments.

1.2 Basic principles of the systems approach

The main principles of the systems approach are:

4. Multiplicity, which allows using a variety of cybernetic, economic and mathematical models to describe individual elements and the system as a whole.

As noted above, with a systematic approach, it is important to study the characteristics of an organization as a system, i.e. "input", "process" characteristics and "output" characteristics.

And, finally, no less important is the study of the parameters of the process that converts resources into finished products. At this stage, depending on the object of study, production technology or management technology is considered, as well as factors and ways to improve it.

system-structural, revealing the internal organization of the system, the way of interaction of its components;

- system-functional, showing what functions the system and its constituent components perform;

system-communication, revealing the relationship of a given system with others, both horizontally and vertically;

system-integrative, showing the mechanisms, factors of conservation, improvement and development of the system;

The system approach is the theoretical and methodological basis of system analysis.

2. Basic elements of system analysis

2. 1 Conceptual apparatus of system analysis

A system analysis of the activities of an enterprise or organization is carried out at the early stages of work on the creation of a specific management system.

The ultimate goal of system analysis is the development and implementation of the selected reference model of the control system.

In accordance with the main goal, it is necessary to carry out the following studies of a systemic nature:

identify general trends in the development of this enterprise and its place and role in the modern market economy;

establish the features of the functioning of the enterprise and its individual divisions;

identify the conditions that ensure the achievement of the goals;

determine the conditions that impede the achievement of goals;

collect the necessary data for analysis and development of measures to improve the current management system;

use the best practices of other enterprises;

study the necessary information to adapt the selected (synthesized) reference model to the conditions of the enterprise in question.

The following characteristics are found in the process of system analysis:

the role and place of this enterprise in the industry;

the state of production and economic activity of the enterprise;

production structure of the enterprise;

management system and its organizational structure;

features of the interaction of the enterprise with suppliers, consumers and higher organizations;

innovative needs (possible connections of this enterprise with research and design organizations;

forms and methods of stimulating and remunerating employees.

Clearly and competently formulated goals for the development of an enterprise (company) are the basis for system analysis and development of a research program.

The system analysis program, in turn, includes a list of issues to be researched and their priority:

1. Analysis of the organizational subsystem, which includes:

policy analysis (objectives);

concept analysis, i.e. systems of views, assessments, ideas for achieving the goals, methods of solution;

analysis of management methods;

analysis of methods of labor organization;

analysis of the structural-functional scheme;

analysis of the system of selection and placement of personnel;

analysis of information flows;

marketing system analysis;

analysis of the security system.

2. Analysis of the economic subsystem and diagnostics of predacceptance.

Based on the analysis and research, a forecast and justification is made for changing and optimizing the existing organizational and economic subsystem of the enterprise.

2.2 Principles of system analysis

System analysis is based on the following principles: 1) unity - a joint consideration of the system as a single whole and as a set of parts;

2) development - taking into account the variability of the system, its ability to develop, accumulate information, taking into account the dynamics of the environment;

3) global goal - responsibility for choosing a global goal. The optimum of subsystems is not the optimum of the entire system;

4) functionality - joint consideration of the structure of the system and functions with the priority of functions over the structure;

5) decentralization - a combination of decentralization and centralization;

6) hierarchies - taking into account the subordination and ranking of parts;

7) uncertainties - taking into account the probabilistic occurrence of an event;

8) organization - the degree of implementation of decisions and conclusions.

combines different methods using a single methodology; based on a scientific worldview;

unites the knowledge, judgments and intuition of specialists in various fields of knowledge and obliges them to a certain discipline of thinking;

focuses on goals and goal setting.

System analysis is located in the middle of this list, since it uses approximately equal proportions of philosophical and methodological ideas (typical for philosophy, systems theory) and formalized methods in the model (which is typical for special disciplines).

Different directions also use the same mathematical methods. At the same time, there are differences between them that determine their choice in specific decision-making situations. In particular, the main specific features of system analysis that distinguish it from other system areas are:

System analysis can be performed in the following sequence:

1. Statement of the problem - the starting point of the study. In the study of a complex system, it is preceded by work on structuring the problem.

2. Expansion of the problem to a problematic, i.e. finding a system of problems that are essentially related to the problem under study, without taking into account which it cannot be solved.

3. Identification of goals: goals indicate the direction in which to move in order to solve the problem in stages.

System analysis is based on the following principles:
1) unity - a joint consideration of the system as a single whole and as a set of parts;

support an idea of any kind, even if its relevance seems doubtful to you at the moment;

Kuzmin V.P. Historical background and epistemological foundations
systemic approach. - Psychol. journal, 1982, vol. 3, no. 3, p. 3 - 14; No. 4, p. 3 - 13.