Principles and methods of system analysis. Expansion of the problem to the problematics, t

Date: 29.09.2019

System analysis- a scientific method of cognition, which is a sequence of actions to establish structural links between the elements of the studied complex systems - technical, economic, etc. It relies on a complex of general scientific, experimental, natural science, statistical, mathematical methods. It is carried out using modern computer technology. The result of systemic research is, as a rule, the choice of a well-defined alternative: a development plan, a technical system, a region, a commercial structure, etc. Therefore, the origins of systems analysis, its methodological concepts lie in those disciplines that deal with the problems of decision-making: the theory of operations and the general theory of management and the systems approach.

The goal of systems analysis is to streamline the sequence of actions in solving large problems, based on a systems approach. In systems analysis, problem solving is defined as an activity that maintains or improves the performance of a system. Techniques and methods of system analysis are aimed at putting forward alternative solutions to the problem, identifying the scale of uncertainty for each option and comparing options for their effectiveness.

System analysis is based on a number of general principles, including:

the principle of deductive sequence - a sequential consideration of the system in stages: from the environment and connections with the whole to the connections of the parts of the whole (see the stages of system analysis for more details below);

the principle of integrated consideration - each system should be integral as a whole, even when considering only individual subsystems of the system;

the principle of coordinating resources and goals of consideration, updating the system;

the principle of non-conflict - the absence of conflicts between parts of the whole, leading to a conflict of goals of the whole and the part.

2. Application of system analysis

The area of application of the methods of system analysis is very wide. There is a classification according to which all problems, to the solution of which the methods of system analysis can be applied, are divided into three classes:

well-structured or quantified problems in which the essential relationships are very well understood;

unstructured (unstructured), or qualitatively expressed problems containing only a description of the most important resources, signs and characteristics, the quantitative relationships between which are completely unknown;

poorly structured (ill-structured), or mixed problems that contain both qualitative elements and little-known, vague sides that tend to dominate.

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

Involvement of methods of system analysis to solve these problems is necessary, first of all, because in the decision-making process one has to make a choice under conditions of uncertainty, which is due to the presence of factors that cannot be rigorously quantified. In this case, all procedures and methods are aimed precisely at proposing alternative solutions to the problem, identifying the scale of uncertainty for each of the options and comparing the options according to one or another performance criterion. Experts only prepare or recommend solutions, while making a decision remains in the competence of the relevant official (or body).

Decision support systems are used to solve poorly structured and unstructured problems.

The technology for solving such complex problems can be described by the following procedure:

the formulation of the problem situation;

defining goals;

determination of criteria for achieving goals;

building models to justify decisions;

search for the optimal (acceptable) solution;

approval of a solution;

preparation of a solution for implementation;

approval of the decision;

managing the progress of the solution implementation;

checking the effectiveness of the solution.

The central procedure in systems analysis is the construction of a generalized model (or models) that reflects all the factors and relationships of a real situation that may appear in the process of implementing a solution. The resulting model is investigated in order to find out the proximity of the result of applying one or another of the alternative options of action to the desired one, the comparative costs of resources for each of the options, the degree of sensitivity of the model to various external influences.

Research is based on a number of applied mathematical disciplines and methods widely used in modern technical and economic management-related activities. These include:

methods of analysis and synthesis of control theory systems,

method of expert assessments,

critical path method,

queuing theory, etc.

The technical basis of system analysis is modern computing power and information systems created on their basis.

Methodological tools used in solving problems using systems analysis are determined depending on whether a single goal or a set of goals is being pursued, whether a decision is made by one person or several, etc. When there is one sufficiently clearly expressed goal, the degree of achievement of which can be assessed on the basis of one criterion, methods of mathematical programming are used. If the degree of goal achievement is to be assessed on the basis of several criteria, the apparatus of the theory of utility 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.

Despite the fact that the range of modeling and problem solving methods used in systems analysis is constantly expanding, it is not identical in nature to scientific research: it is not associated with the tasks of obtaining scientific knowledge in the proper sense, but is only the application of scientific methods to solving practical problems. management and pursues the goal of rationalizing the decision-making process, not excluding from this process subjective moments inevitable in it.

System Analysis - it is a system theory methodology, which consists in the study of any objects represented as systems, their structuring and subsequent analysis. main feature

system analysis lies in the fact that it includes not only methods of analysis (from the Greek. analysis - dismemberment of an object into elements), but also methods of synthesis (from the Greek. synthesis - connection of elements into a single whole).

The main goal of systems analysis is to detect and eliminate uncertainty in solving a complex problem based on finding the best solution from the existing alternatives.

A problem in systems analysis is a complex theoretical or practical issue that needs to be addressed. At the heart of any problem is the resolution of a contradiction. For example, the choice of an innovative project that would meet the strategic goals of the enterprise and its capabilities is a certain problem. Therefore, the search for the best solutions when choosing innovative strategies and tactics of innovative activity should be carried out on the basis of a system analysis. The implementation of innovative projects and innovative activities is always associated with elements of uncertainty that arise in the process of nonlinear development, both of these systems themselves and of the systems of the environment.

The methodology of systems analysis is based on the operations of quantitative comparison and selection of alternatives in the process of making a decision to be implemented. If the requirement of quality criteria for alternatives is met, then their quantitative estimates can be obtained. In order for quantitative assessments to make it possible to compare alternatives, they must reflect the criteria for choosing alternatives participating in the comparison (result, efficiency, cost, etc.).

In systems analysis, problem solving is defined as an activity that maintains or improves the characteristics of a system or creates a new system with specified qualities. Techniques and methods of system analysis are aimed at developing alternative options for solving the problem, identifying the scale of uncertainty for each option and comparing options for their effectiveness (criteria). Moreover, the criteria are built on a priority basis. System analysis can be represented as a set of basic logical elements:

- the purpose of the study is to solve a problem and obtain a result;
- resources - scientific means of solving the problem (methods);
- alternatives - options for solutions and the need to choose one of several solutions;
- criteria - a means (sign) for assessing the solvability of the problem;
- a model for creating a new system.

Moreover, the formulation of the goal of system analysis plays a decisive role, since it gives a mirror image of the existing problem, the desired result of its solution and a description of the resources with which this result can be achieved (Fig. 4.2).

Rice. 4.2.

The goal is concretized and transformed in relation to the performers and conditions. A higher order goal always contains an underlying uncertainty that needs to be taken into account. Despite this, the goal must be specific and unambiguous. Its production must allow the initiative of the performers. "It is much more important to choose the 'right' target than the 'right' system," said Hall, author of a book on systems engineering; "choosing the wrong goal means solving the wrong problem; and choosing the wrong system means just choosing a non-optimal system."

If the available resources cannot ensure the implementation of the set goal, then we will get unplanned results. The goal is the desired result. Therefore, to achieve the goals, appropriate resources must be selected. If resources are limited, then it is necessary to adjust the goal, i.e. plan for the results that can be obtained with a given set of resources. Therefore, the formulation of goals in innovation should have specific parameters.

The main tasks system analysis:

decomposition problem, i.e. decomposition of the system (problem) into separate subsystems (tasks);
the task of the analysis is to determine the laws and patterns of system behavior by detecting system properties and attributes;
the problem of synthesis leads to the creation of a new model of the system, the determination of its structure and parameters on the basis of the knowledge and information obtained in solving problems.

The general structure of the system analysis is presented in table. 4.1.

Table 4.1

The main tasks and functions of system analysis

System analysis framework
decomposition
Definition and decomposition of a common goal, main function	Functional structural analysis	Development of a new system model
Isolating the system from the environment	Morphological analysis (analysis of the relationship of components)	Structural synthesis
Description of influencing factors	Genetic analysis (analysis of background, trends, forecasting)	Parametric synthesis
Description of development trends, uncertainties	Analog Analysis	Assessing the new system
Description as "black box"	Efficiency analysis
Functional, component and structural decomposition	Formation of requirements for the system being created

In the concept of system analysis, the process of solving any complex problem is considered as a solution to a system of interrelated problems, each of which is solved by its own subject methods, and then the synthesis of these solutions is performed, assessed by the criterion (or criteria) for achieving the solvability of this problem. The logical structure of the decision-making process within the framework of system analysis is shown in Fig. 4.3.

Rice. 4.3.

In innovation, there can be no ready-made models of solutions, since the conditions for the implementation of innovations can change, a technique is needed that allows at a certain stage to form a model of a solution that is adequate to existing conditions.

To make "balanced" design, managerial, social, economic and other decisions, a wide coverage and comprehensive analysis of factors that significantly affect the problem being solved is required.

Systems analysis is based on many principles that define its main content and distinguish it from other types of analysis. It is necessary to know, understand and apply this in the process of implementing a systematic analysis of innovation.

These include the following principles :

1) the ultimate goal - the formulation of the research goal, the definition of the main properties of a functioning system, its purpose (goal-setting), quality indicators and criteria for assessing the achievement of the goal;
2) measurements. The essence of this principle is the comparability of the system parameters with the parameters of the higher-level system, i.e. external environment... The quality of the functioning of any system can be judged only in relation to its results to the supersystem, i.e. to determine the effectiveness of the functioning of the system under study, it is necessary to present it as a part of a higher-level system and evaluate its results in relation to the goals and objectives of the supersystem or the environment;
3) equifinality - determining the form of sustainable development of the system in relation to the initial and boundary conditions, i.e. determination of its potential capabilities. The system can reach the required final state regardless of time and is determined solely by its own characteristics of the system under different initial conditions and in different ways;
4) unity - consideration of the system as a whole and a set of interrelated elements. The principle is focused on "looking inside" the system, on dividing it while preserving integral ideas about the system;
5) interconnections - procedures for determining relationships, both within the system itself (between elements) and with the external environment (with other systems). In accordance with this principle, the system under study, first of all, should be considered as a part (element, subsystem) of another system, called a supersystem;
6) modular construction - the allocation of functional modules and a description of the totality of their input and output parameters, which avoids unnecessary detail to create an abstract model of the system. Allocation of modules in the system allows you to consider it as a set of modules;
7) hierarchies - determination of the hierarchy of functional and structural parts of the system and their ranking, which simplifies the development of a new system and establishes the procedure for its consideration (research);
8) functionality - a joint consideration of the structure and functions of the system. If new functions are introduced into the system, the new structure should also be developed rather than incorporating new functions into the old structure. Functions are associated with processes that require the analysis of various flows (material, energy, information), which in turn affects the state of the elements of the system and the system itself as a whole. The structure always limits flows in space and in time;
9) development - determining the patterns of its functioning and potential for development (or growth), adaptation to changes, expansion, improvement, embedding new modules based on the unity of development goals;
10) decentralization - a combination of centralization and decentralization functions in the management system;
11) uncertainty - taking into account the factors of uncertainty and random factors of influence, both in the system itself and from the external environment. Identification of uncertainty factors as risk factors allows their analysis and creation of a risk management system.

The principle of the final goal serves to determine the absolute priority of the final (global) goal in the process of conducting a system analysis. This principle dictates the following regulations:

1) first it is necessary to formulate the objectives of the research;
2) the analysis is carried out based on the main purpose of the system. This makes it possible to determine its main essential properties, quality indicators and evaluation criteria;
3) in the process of synthesis of solutions, any changes must be assessed from the standpoint of achieving the final goal;
4) the purpose of the functioning of an artificial system is set, as a rule, by a supersystem in which the system under study is an integral part.

The process of implementing a system analysis in solving any problem can be characterized as a sequence of main stages (Fig. 4.4).

Rice. 4.4.

At the stage decomposition carried out:

1) determination and decomposition of the general goals of solving the problem, the main function of the system as a limitation of development in space, the state of the system or the area of acceptable conditions of existence (the goal tree and the function tree are determined);
2) the separation of the system from the environment according to the criterion of participation of each element of the system in the process leading to the desired result based on the consideration of the system as an integral part of the supersystem;
3) definition and description of influencing factors;
4) description of development trends and uncertainties of various types;
5) description of the system as a "black box";
6) decomposition of the system according to a functional criterion, according to the type of elements included in it, but structural features (according to the type of relations between elements).

The level of decomposition is determined based on the set research goal. Decomposition is carried out in the form of subsystems, which can be a serial (cascade) connection of elements, parallel connection of elements and connection of elements with feedback.

At the stage analysis a detailed study of the system is carried out, which includes:

1) functional and structural analysis of the existing system, which allows formulating the requirements for the new system. It includes clarification of the composition and regularities of the functioning of elements, algorithms for the functioning and interaction of subsystems (elements), separation of controlled and uncontrolled characteristics, setting the state space, time parameters, analyzing the integrity of the system, forming requirements for the system being created;
2) analysis of interconnections of components (morphological analysis);
3) genetic analysis (background, reasons for the development of the situation, existing trends, making forecasts);
4) analysis of analogs;
5) analysis of the effectiveness of results, use of resources, timeliness and efficiency. The analysis includes the choice of measurement scales, the formation of indicators and performance criteria, the evaluation of the results;
6) formulation of requirements for the system, formulation of criteria for assessment and limitations.

During the analysis, use different ways solving problems.

At the stage synthesis :

1) a model of the required system will be created. This includes: a certain mathematical apparatus, modeling, evaluation of the model for adequacy, efficiency, simplicity, inaccuracies, balance between complexity and accuracy, various implementation options, blockiness and consistency of construction;
2) synthesis of alternative structures of the system is made, allowing to solve the problem;
3) synthesis of various parameters of the system is performed in order to eliminate the problem;
4) an assessment of the variants of the synthesized system is carried out with the justification of the assessment scheme itself, the processing of the results and the choice of the most effective solution;
5) the assessment of the degree of solution of the problem is carried out at the end of the system analysis.

As for the methods of system analysis, they should be considered in more detail, since their number is large enough and suggests the possibility of their use in solving specific problems in the process of problem decomposition. A special place in systems analysis is occupied by the modeling method, which implements the principle of adequacy in systems theory, i.e. description of the system as an adequate model. Model - ego is a simplified semblance of a complex object-system in which its characteristic properties are preserved.

In system analysis, the modeling method plays a decisive role, since any real complex system in research and design can only be represented by a certain model (conceptual, mathematical, structural, etc.).

System analysis uses special methods modeling:

- simulation modeling, based on statistical methods and programming languages;
- situational modeling, based on the methods of set theory, theory of algorithms, mathematical logic and presentation of problem situations;
- information modeling, based on mathematical methods of the theory of the information field and information chains.

In addition, the methods of induction and reduction modeling are widely used in systems analysis.

Induction modeling is carried out in order to obtain information about the specifics of the object-system, its structure and elements, ways of their interaction based on the analysis of the particular and bringing this information to a general description. The inductive method for modeling complex systems is used when it is impossible to adequately represent the model of the internal structure of an object. This method allows you to create a generalized model of an object-system, while maintaining the specificity of organizational properties, connections and relationships between elements, which distinguishes it from another system. When constructing such a model, the methods of logic of the theory of probability are often used, i.e. such a model becomes logical or hypothetical. Then the generalized parameters of the structural and functional organization of the system are determined and their regularities are described using the methods of analytical and mathematical logic.

Reduction modeling is used to obtain information about the laws and patterns of interaction in a system of various elements in order to preserve the whole structural formation.

With this method of research, the elements themselves are replaced by a description of their external properties. The use of the method of reduction modeling allows solving problems of determining the properties of elements, the properties of their interaction and the properties of the structure of the system itself, in accordance with the principles of the whole formation. This method is used to find methods for decomposing elements and changing the structure, giving the system as a whole new qualities. This method meets the goals of synthesizing the properties of the system based on the study of the internal potential for change. The practical result of using the synthesis method in reduction modeling is a mathematical algorithm for describing the processes of interaction of elements in the whole education.

The main methods of system analysis represent a set of quantitative and qualitative methods that can be presented in the form of a table. 4.2. According to the classification of V.N. Volkova and A.A. Denisov, all methods can be divided into two main types: methods of formal representation of systems (MFPS) and methods and methods of activating the intuition of specialists (MAIS).

Table 4.2

System analysis methods

Consider the content of the main methods of formal representation of systems that use mathematical tools.

Analytical methods, including methods of classical mathematics: integral and differential calculus, search for extrema of functions, calculus of variations; mathematical programming; methods of game theory, theory of algorithms, theory of risks, etc. These methods make it possible to describe a number of properties of a multidimensional and multiply connected system, displayed as a single point moving in n -dimensional space. This mapping is done using the function f (s ) or by means of an operator (functional) F (S ). It is also possible to display by points two or more systems or their parts and to consider the interaction of these points. Each of these points makes a movement and has its own behavior in n -dimensional space. This behavior of points in space and their interaction are described by analytical laws and can be represented in the form of quantities, functions, equations, or a system of equations.

The use of analytical methods is conditioned only when all system properties can be represented in the form of deterministic parameters or dependencies between them. It is not always possible to obtain such parameters in the case of multicomponent, multicriteria systems. This requires a preliminary determination of the degree of adequacy of the description of such a system using analytical methods. This, in turn, requires the use of intermediate, abstract models that can be investigated by analytical methods, or the development of completely new systemic methods of analysis.

Statistical Methods are the basis of the following theories: probabilities, mathematical statistics, operations research, statistical simulation, queuing, including the Monte Carlo method, etc. Statistical methods allow you to display the system using random (stochastic) events, processes that are described by the corresponding probabilistic (statistical) characteristics and statistical patterns. Statistical methods are used to study complex non-deterministic (self-developing, self-governing) systems.

Set-theoretic methods, according to M. Mesarovich, serve as the basis for the creation of a general theory of systems. Using such methods, the system can be described in universal terms (set, element of a set, etc.). When describing, it is possible to introduce any relationship between elements, guided by mathematical logic, which is used as a formal descriptive language of relationships between elements of different sets. Set-theoretic methods make it possible to describe complex systems in a formal modeling language.

It is advisable to use such methods in cases where complex systems cannot be described by methods of one subject area. Set-theoretical methods of systems analysis are the basis for the creation and development of new programming languages and the creation of computer-aided design systems.

Logical methods are the language for describing systems in terms of the algebra of logic. Logical methods are most widely used under the name of Boolean algebra as a binary representation of the state of the elementary circuits of a computer. Logical methods allow describing the system in the form of more simplified structures based on the laws of mathematical logic. On the basis of such methods, new theories of formal description of systems in the theories of logical analysis and automata are being developed. All these methods expand the possibility of applying systems analysis and synthesis in applied informatics. These methods are used to create models of complex systems that are adequate to the laws of mathematical logic to build stable structures.

Linguistic methods. With their help, special languages are created that describe systems in the form of thesaurus concepts. A thesaurus is a set of semantic-expressing units of a certain language with a system of semantic relations given on it. Such methods have found their application in applied informatics.

Semiotic methods are based on the concepts: symbol (sign), sign system, sign situation, i.e. used to symbolically describe content in information systems.

Linguistic and semiotic methods have become widely used in the case when for the first stage of the study it is impossible to formalize decision-making in poorly formalized situations and analytical and statistical methods cannot be used. These methods are the basis for the development of programming languages, modeling, design automation of systems of varying complexity.

Graphic methods. They are used to display objects in the form of a system image, and also allow you to display in a generalized form system structures and links. Graphic methods are volumetric and linear-planar. Mostly used in the form of Gantt charts, bar charts, charts, charts and pictures. Such methods and the representation obtained with their help make it possible to visually display the situation or the decision-making process in changing conditions.

Alekseeva M.B. Systems approach and systems analysis in economics.

Alekseeva M.B., Balan S.N. Foundations of systems theory and systems analysis.

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Introduction

1. System analysis

Conclusion

Bibliography

Introduction

From a practical point of view, systems analysis is a universal technique for solving complex problems of an arbitrary nature, where the concept of "problem" is defined as "the subjective negative attitude of the subject to reality." The difficulty in diagnosing the 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 the research conducted by the systems analyst.

Over time, systems analysis has become an inter- and over-disciplinary course, generalizing the methodology of 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, it becomes more and more important to use systems analysis.

Western authors (J. van Gig, R. Ashby, R. Ackoff, F. Emery, S. Beer) are mostly inclined towards applied systems analysis, its application for 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 systems analysis, as a framework of increasing scientific knowledge, to the definition of philosophical categories "system "," Element "," part "," whole ", etc.

System analysis requires further research 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; the formation of the theory of systemic-structural synthesis; development of methods for organizing complex examinations.

The elaboration of the topic "system analysis" is quite large: many scientists, researchers, philosophers were engaged in the concept of systemicity. However, it should be noted that there is an insufficient number of complete and explicit theories for studying the topic of its application in management.

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

The aim of the work is to identify the main stages of development and formation of systems analysis.

This goal makes it necessary to solve the following main tasks:

Study the history of development and change in system analysis;

Consider the methodology of systems analysis;

To study and analyze the possibilities of implementing systems analysis.

1. System analysis

1.1 System Analysis Definitions

Systems analysis is the further development of a number of disciplines, such as operations research, optimal control theory, decision-making theory, expert analysis, system operation organization theory, etc. To successfully solve the assigned tasks, system analysis uses the entire set of formal and informal procedures. The listed theoretical disciplines are the basis and methodological basis of systems analysis. Thus, systems 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 systems analysis, and most importantly, their successful application in practice became possible only with the introduction and widespread use of computers. Ackoff R. On purposeful systems / R. Ackoff, 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 the construction of theoretical models of systems to their widespread practical application. In this regard, N.N. Moiseev writes that systems 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 systems analysis is the problem of decision making.

With regard to the problems of research, design and management of complex systems, the decision-making problem is associated with the choice of a certain alternative in conditions of various kinds of uncertainty. Uncertainty is due to the multi-criteria nature of optimization problems, the uncertainty of the development goals of the systems, the ambiguity of the system development scenarios, the lack of a priori information about the system, the influence 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 the problems of decision-making in conditions when the choice of an alternative requires the analysis of complex information of various physical nature... Volkova, V.N. System analysis and its application in ACS / V.N. Volkova, A.A. Denisov. - L .: LPI, 2008 .-- 83 p.

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

1) building a model of the investigated object;

2) statement of the research problem;

3) solution of the set mathematical problem.

Let's consider these stages.

Since knowledge is always relative, a description in any language reflects only some aspects of the processes taking place 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. The desire to reflect all aspects of the existence of the system when constructing a model of a system is deeply mistaken. When conducting a system analysis, as a rule, people are interested in the dynamic behavior of the system, and when describing the dynamics from the point of view of the research being conducted, there are primary parameters and interactions, but there are parameters that are insignificant in this study. Thus, the quality of the model is determined by the compliance of the performed description with the requirements for research, the compliance of the results obtained using the model with the course of the observed process or phenomenon. The construction of a mathematical model is the basis of all systems analysis, the central stage in the study or design of any system. The result of the entire system analysis depends on the quality of the model. Bertalanffy L. Background. General Systems Theory: A Critical Review / L. Bertalanffy. Von // Research on General Systems Theory. - M .: Progress, 2009 .-- S. 23 - 82.

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 research. The goal should be formalized. The task of the system analysis is to carry out necessary analysis uncertainties, restrictions and the formulation, ultimately, of some optimization problem

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

Solution of the posed mathematical problem

Only this third stage of analysis can be attributed to the stage itself, which is used in full extent mathematical methods... Although without knowledge of mathematics and the capabilities of its apparatus, the successful implementation of the first two stages is impossible, since both when building a model of the system and when formulating the goal and objectives of analysis wide application should find methods of formalization. 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 tasks of system analysis can have a number of features that lead to the need to use, along with formal procedures, heuristic approaches. 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. The successful solution of the problems of systems 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 research goal turns into a major theoretical problem.

1.2 Characteristics of the tasks of system analysis

Systems 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 systems 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 the system analysis, not yet having had time 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 insufficiently developed and tested methods and results and is not able to postpone the solution of related tasks until tomorrow. This is the source of both the strength and the weakness of system analysis: strength - because it constantly feels the impact of the needs of practice, is forced to continuously expand the range of research objects, and has no opportunity to abstract from the real needs of society; weaknesses - because often the use of "raw", insufficiently developed methods of systemic research leads to the adoption of hasty decisions, neglect of real difficulties. Clear, D. Systemology / D. Clear. - M .: Radio and communication, 2009 .-- 262 p.

Let us consider the main tasks to be solved 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 the boundary between the system under study and the environment, which predetermines the maximum depth of influence of the considered interactions, which the consideration is limited to;

Determination of the real resources of such interaction;

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

Problems of the next type are associated with the construction 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 for enhancing the inductive capabilities of human thinking, in contrast to its deductive capabilities, which, in fact, is 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 directions can be distinguished here, such as the development of the formal apparatus of inductive logic, methods of morphological analysis and other structural and syntactic methods for constructing new alternatives, methods of synthetics and the 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 the construction of a set of simulation models that describe the influence of this or that interaction on the behavior of the object of research. It should be noted that the goal of creating a kind of supermodel is not pursued in systemic studies. 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 the 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 systemic study is associated with the study of various alternatives for the development of the system. The task of system analysts is to select and justify the best development alternative. At the stage of developing and making decisions, 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 decision-making theory and the formation of target structures, programs and plans. There is no shortage of works and active 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 at hand and the means of their solution. Research in this area includes: Volkova, V.N. System analysis and its application in ACS / V.N. Volkova, A.A. Denisov. - L .: LPI, 2008 .-- 83 p.

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

b) solving the problem of multicriteria in assessing the alternatives of decision or planning;

c) investigating the problem of uncertainty, especially associated not with factors of a statistical nature, but with the uncertainty of expert judgments and deliberately created uncertainty associated with the simplification of 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 the specific features of socio-economic criteria of efficiency;

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

The latter direction requires a new understanding of the real functions of 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 a complete list of tasks. These are the ones that are most difficult to solve. 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 the composition of the performers. Moreover, in order to solve all these problems, a researcher must have a broad outlook and possess a rich arsenal of methods and means of scientific research. Anfilatov, V.S. System analysis in management: textbook. manual / V.S. Anfilatov and others; ed. A.A. Emelyanov. - M .: Finance and statistics, 2008 .-- 368 p.

The ultimate goal of system analysis is to resolve a problematic situation that has arisen in front of the object of the system research being carried out (usually this 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 that resolves the problem situation. The initial stage of any systemic research is the study of the object of the system analysis being carried out with its subsequent formalization. At this stage, problems arise that fundamentally distinguish the methodology of systems research from the methodology of other disciplines, namely, a two-pronged problem is solved in systems analysis. On the one hand, it is necessary to formalize the object of systemic research, on the other hand, the process of studying the system, the process of formulating and solving a problem, is subject to formalization. Here's 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 (basically, its structural organization is subject to formalization) and its behavior in time (dynamic aspects that reflect its functioning) are solved. Second, the design process needs to be formalized. The constituent parts of the design process are methods for the formation of various design solutions, methods of their engineering analysis and decision-making methods for choice. best options system implementation.

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, let us note such an aspect as the influence of unknown factors on the system.

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

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

The purpose of the goal, the choice of criterion, and the formalization of the goal are almost always a difficult problem. Problems with many criteria are typical for large technical, economic, and economic projects.

And, finally, one should note such a type of uncertainty as the uncertainty associated with the subsequent influence of the results of the decision made on the problem situation. The point is that the decision taken at the moment and implemented in a certain system is designed to affect the functioning of the system. Actually, this is why it is accepted, since, according to the idea of system analysts, this decision should resolve the problem situation. However, since the decision is made for a complex system, the development of the system over time can have many strategies. And, of course, at the stage of forming a decision and making a control action, analysts may not imagine a complete picture of the development of the situation. Anfilatov, V.S. System analysis in management: textbook. manual / 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 "problems" in systems analysis

From a practical point of view, systems analysis 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 the system analysis, as well as the methods and algorithms that will be used in the future to support decision-making. At the same time, this stage is the most difficult and least formalized.

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

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

With this approach, the "problem" is defined as the discrepancy between the actual and the desired, that is, the 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 exclusively as that part objective reality to be compared with the reference model.

If we rely on the concept of “problem”, then we can conclude that with a rational approach, the problem arises only for a system analyst who has a certain formal model of a certain system, finds this system and reveals 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 ACS / V.N. Volkova, A.A. Denisov. - L .: LPI, 2008 .-- 83 p.

Obviously, there are systems, the organization and behavior of which is strictly regulated and recognized by all actors - for example, legal laws... The discrepancy between the model (law) and reality in this case is a problem (offense) that needs to be solved. However, for most artificial systems, strict regulations do not exist, and subjects have their own personal goals in relation to such systems, which rarely coincide with the goals of other subjects. Moreover, a specific subject has his own idea of which system he is a part of, with which systems he interacts. The concepts, which the subject operates, can radically differ from the "rational" generally accepted ones. For example, a subject may not isolate a control system from the environment at all, but use a certain understandable and convenient model of interaction with the world 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 therefore to the emergence of new problems, which fundamentally contradicts the very essence of system analysis, which assumes an improving effect - 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 systems analysis in a rational approach is expressed in terms of an optimization problem, that is, the problem situation is idealized to a level that allows the use of mathematical models and quantitative criteria to determine the best option for solving the problem.

As you know, for a systemic problem there is no model that exhaustively establishes causal relationships between its components, therefore the optimization approach does not seem quite constructive: the search for a really achievable (compromise) option for resolving the problem, when the desired can be waived 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 implies the use of situational preference criteria, that is, criteria that are not initial attitudes, but are developed in the course of the study ... ”.

Another area of systems analysis - the objective-subjective approach, based on the works of Ackoff, puts the concept of a subject and a 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 examines objectively observable facts and patterns.

Let's go back to the definition of "problem". From it, in particular, it follows that when we observe the 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 to be solved. Although this fact does not contradict the concept of a “problem”, 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 subject's problem:

* 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.

There are several reasons why the subject may not have a "negative attitude to reality": Director, C. Introduction to systems theory / S. Director, D. Rorar. - M .: Mir, 2009 .-- 286 p.

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

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

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

* does not believe in information about the existence of problems and their essence, because believes that the people who report it slander his activities or pursue their own selfish interests, and maybe because he simply personally does not like these people.

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

Since identifying a problem requires an analysis of a subjective attitude, this stage refers to the non-formalized stages of system analysis.

No effective algorithms or techniques have been proposed at the moment, most often the authors of works on systems analysis rely on the analyst's experience and intuition and offer him complete freedom of action.

The systems analyst must have a sufficient set of tools for describing and analyzing that part of objective reality with which the subject interacts or can interact. Tools may include methods for experimental investigation 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 registered and stored in databases, which already 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. We can say that today, when analyzing most artificial systems, the analyst is more likely to face a lack of effective methods for studying systems than with a lack of information about the system.

However, it is the subject who must formulate the subjective attitude, 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, the knowledge about the system and predictive models that the analyst will eventually receive should be presented in an explicit form that can be interpreted (possibly in natural language). Such a view can be called knowledge about the system under study.

Unfortunately, no effective methods of gaining knowledge about the system have been proposed at the moment. Of greatest interest are Data Mining models and algorithms, 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 use of the idea of a multidimensional conceptual representation.

But in recent years, due to the growing problem of "information overload", more and more researchers use and improve Data Mining methods to solve the problems of knowledge extraction.

The widespread use of knowledge extraction methods is very difficult, which, on the one hand, is associated with the insufficient efficiency of most of the known approaches, which are based on sufficiently formal mathematical and statistical methods, and, on the other hand, with the difficulty of using effective methods of intelligent 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 data analysis and knowledge extraction about the system, based on the automated generation and configuration of intelligent information technologies. This approach will allow, firstly, through the use of advanced intelligent technologies, to significantly increase the efficiency of solving the problem of extracting knowledge, which will be presented to the subject at the stage of identifying the problem in the system analysis. Secondly, to eliminate the need for a specialist in setting up and using intelligent technologies, since the latter will be generated and configured in automatic mode. Bertalanffy L. Background. History and status of general systems theory / Bertalanffy L. Von // Systems research: yearbook. - M .: Nauka, 2010 .-- P. 20 - 37.

Conclusion

The formation of systems analysis is associated with the middle of the twentieth century, but in fact, it began to be applied 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 importance in management activities is difficult not to overestimate. Management from the position of a systematic approach is the implementation of a set of actions 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 people who work in the company, and the cultural tradition of the society in which the organization operates. Managers can more easily align their specific work with the work 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 contradictory. In theory, each researcher must find the basic principles and adjust them depending on the situation. Within the framework of the system, it is also possible to 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.

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

Bibliography

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

2. Ackoff, R. On purposeful systems / R. Ackoff, 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. manual / V.S. Anfilatov and others; ed. A.A. Emelyanov. - M .: Finance and statistics, 2008 .-- 368 p.

5. Bertalanffy L. Background. History and status of general systems theory / Bertalanffy L. Von // Systems research: yearbook. - M .: Nauka, 2010 .-- P. 20 - 37.

6. Bertalanffy L. Background. General Systems Theory: A Critical Review / L. Bertalanffy. Von // Research on General Systems Theory. - M .: Progress, 2009 .-- S. 23 - 82.

7. Bogdanov, A.A. General organizational science: textual criticism: in 2 vols. / 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. - SPb .: Publishing house of SPbSTU, 2008.

9. Volkova, V.N. System analysis and its application in ACS / 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 the theory of systems / S. Director, D. Rorar. - M .: Mir, 2009 .-- 286 p.

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

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Tavrichesky Federal University named after IN AND. Vernadsky

Faculty of Mathematics and Computer Science

Abstract on the topic:

"System Analysis"

Completed by a student of 3 courses, 302 groups

Taganov Alexander

supervisor

Stonyakin Fedor Sergeevich

Plan

1. Definition of system analysis

1.1 Building the model

1.2 Statement of the research problem

1.3 Solution of the set mathematical problem

1.4 Characteristics of the tasks of system analysis

3. System analysis procedures

4.1 Formation of the problem

4.2 Setting goals

5. Generating alternatives

Output

Bibliography

1. System Analysis Definitions

Systems analysis as a discipline was formed as a result of the need to research and design complex systems, to manage them in conditions of incompleteness of information, limited resources and lack of time. Systems analysis is the further development of a number of disciplines, such as operations research, optimal control theory, decision-making theory, expert analysis, system operation organization theory, etc. To successfully solve the assigned tasks, system analysis uses the entire set of formal and informal procedures. The listed theoretical disciplines are the basis and methodological basis of systems analysis. Thus, systems 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 systems 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 the construction of theoretical models of systems to their widespread practical application. In this regard, N.N. Moiseev writes that systems 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 systems analysis is the problem of decision making. With regard to the problems of research, design and management of complex systems, the decision-making problem is associated with the choice of a certain alternative in conditions of various kinds of uncertainty. Uncertainty is due to the multi-criteria nature of optimization problems, the uncertainty of the development goals of the systems, the ambiguity of the system development scenarios, the lack of a priori information about the system, the influence 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 the problems of decision-making in conditions when the choice of an alternative requires the analysis of complex information of various physical nature.

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

1) building a model of the investigated object;

2) statement of the research problem;

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

system math generation

1.1 Building the model

The construction of a model (formalization of the studied system, process or phenomenon) is a description of the process in the language of mathematics. When constructing a model, a mathematical description of the phenomena and processes occurring in the system is carried out. Since knowledge is always relative, a description in any language reflects only some aspects of the processes taking place 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. The desire to reflect all aspects of the existence of the system when constructing a model of a system is deeply mistaken. When conducting a system analysis, as a rule, people are interested in the dynamic behavior of the system, and when describing the dynamics from the point of view of the research being conducted, there are primary parameters and interactions, but there are parameters that are insignificant in this study. Thus, the quality of the model is determined by the compliance of the performed description with the requirements for research, the compliance of the results obtained using the model with the course of the observed process or phenomenon. The construction of a mathematical model is the basis of all systems analysis, the central stage in the study 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 research. The goal should be formalized. The task of systems analysis is to carry out the necessary analysis of uncertainties, constraints and, ultimately, formulate some optimization problem.

Here NS - an element of some normalized 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 problem of systems analysis at this stage is treated as some kind of optimization problem. By analyzing the system requirements, i.e. goals that the researcher intends to achieve, and those uncertainties that are inevitably present, the researcher must formulate the goal of analysis in the language of mathematics. The optimization language turns out to be natural and convenient here, but it is by no means the only possible one.

1.3 Solution of the set mathematical problem

Only this third stage of analysis can be attributed to the stage itself, which fully uses 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 in building a model of the system and in 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 tasks of system analysis can have a number of features that lead to the need to use, along with formal procedures, heuristic approaches. 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 NS and the complexity of the structure of the set G... In this case, the difficulties arising from the need to apply informal analysis procedures are often decisive. The successful solution of the problems of systems 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 research goal turns into a major theoretical problem.

1.4 Characteristics of the tasks of system analysis

Systems 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 systems 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 had time 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 insufficiently developed and tested methods and results and is not able to postpone the decision 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 needs of practice, is forced to continuously expand the range of research objects and has no opportunity to abstract from the real needs of society; weaknesses - because often the use of "raw", insufficiently developed methods of systemic research leads to the adoption of hasty decisions, neglect of real difficulties.

Let us consider the main tasks to solve 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 the boundary between the system under study and the environment, which predetermines the maximum depth of influence of the considered interactions, which are limited to the consideration;

· Determination of real resources of such interaction;

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

Problems of the next type are associated with the construction 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 for enhancing the inductive capabilities of human thinking, in contrast to its deductive capabilities, which, in fact, is 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 directions can be distinguished here, such as the development of the formal apparatus of inductive logic, methods of morphological analysis and other structural and syntactic methods for constructing new alternatives, methods of syntactics 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 the construction of a set of simulation models that describe the influence of this or that interaction on the behavior of the object of research. Note that in systemic studies, the goal of creating a certain supermodel is not pursued. 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 investigated, the question of how to combine various aspects of the system's behavior into a certain unified 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 analogous objects and transferring the results of these studies to the object of system analysis. Such a study provides a basis for a meaningful understanding of the 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 formed plans and programs; b) solving the problem of multicriteria in assessing the alternatives of decision or planning;

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

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

d) study of the specific features of 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 predeterminedness of the action program and its readiness for restructuring when new information arrives, both about external events and changes in ideas about the implementation of this program.

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

2. Features of system analysis tasks

The ultimate goal of system analysis is to resolve a problematic situation that has arisen in front of the object of the system research being carried out (usually this 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 that resolves the problem situation. The initial stage of any systemic research is the study of the object of the system analysis being carried out with its subsequent formalization. At this stage, problems arise that fundamentally distinguish the methodology of systems research from the methodology of other disciplines, namely, a two-pronged problem is solved in systems analysis. On the one hand, it is necessary to formalize the object of systemic research, on the other hand, the process of studying the system, the process of formulating and solving a problem, is subject to formalization. Here's 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 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 (basically, its structural organization is subject to formalization) and its behavior in time (dynamic aspects that reflect its functioning) are solved. Second, the design process needs to be formalized. The constituent parts of the design process are methods of forming various design solutions, methods of their engineering analysis and methods of making decisions on 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 of optimality of the decisions made. Currently, it is necessary to solve the 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 such a level that the creation of a simply workable structure by itself no longer always satisfies the leading industries. It is necessary during the design to ensure best performance for a number of characteristics of new products, for example, to achieve maximum performance, minimum dimensions, cost, etc. while maintaining all other requirements within the specified limits. Thus, practice makes demands on the development of not just a workable product, object, system, but the creation of an optimal project. Similar reasoning is valid for other types of activities. When organizing the functioning of an enterprise, requirements are formulated to maximize the efficiency of its activities, the reliability of the equipment, optimize the strategies for servicing systems, allocating resources, etc.

In various areas 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 predetermine 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, let us note such an aspect as the influence of unknown factors on the system.

Uncertainty due to unknown factors also comes in different forms. The simplest kind 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 on the basis of an analysis of the past experience of the functioning of the object of systemic research.

The next kind of uncertainty is ambiguity of goals... The formulation of a goal in solving problems of system analysis is one of the key procedures, because the goal is an object that determines the formulation of the problem of systemic research. The ambiguity of the goal is a consequence of the multicriteria of the tasks of system analysis. The purpose of the goal, the choice of criterion, and the formalization of the goal are almost always a difficult problem. Problems with many criteria are typical for large technical, economic, and economic projects.

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

As the next feature of systems analysis, we note the role of models as a means of studying systems that are the object of systems research. Any methods of system analysis are based on a 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 conformity of the model to those requirements that are imposed on the study, the conformity 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 a model, one speaks of mathematical models. The construction of a mathematical model is the basis of all systems analysis. This is the central stage in the research or design of any system. The success of all subsequent analysis depends on the quality of the model. However, in system analysis, along with formalized procedures, informal, heuristic research methods occupy an important place. There are a number of reasons for this. The first is as follows. When constructing models of systems, there may be a lack or lack of initial information for determining the parameters of the model.

In this case, an expert survey of specialists is carried out in order to eliminate uncertainty or, at least, to 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 taking place 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 described phenomena. In other words-

mi, the desire to adapt a well-studied mathematical apparatus to describe the phenomena under study can distort their essence and lead to wrong 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 the algorithms for constructing a model and methods of their research is used, which does not lend itself to formal analysis. Heuristic methods for finding solutions are formed by a person or a group of researchers in the process of their creative activity. A heuristic is a collection of knowledge, experience, intelligence used to obtain solutions using informal rules. Heuristic methods turn out to be useful and even irreplaceable in studies that are non-numerical in nature or differ in complexity, uncertainty, and variability.

Surely, when considering specific tasks of system analysis, it will be possible to highlight some of their features, but, in the author's opinion, the features noted here are common to all tasks of systems research.

3. System analysis procedures

In the previous section, three stages of the systems analysis were formulated. These stages are the basis for solving any problem of conducting system research. Their essence lies in the fact 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 the research task and further solve the task. These three stages of the system analysis are an enlarged scheme for solving the problem. In reality, the tasks of systems analysis are quite complex, so the enumeration of the stages cannot be an end in itself. We also note that the systems 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 be successful in achieving them. There have been numerous attempts to create a fairly general, universal system analysis algorithm. 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 system analysis algorithm, which are a generalization of the sequence of stages of such an analysis, formulated by a number of authors, and reflect its general laws.

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;

· Research of resource opportunities;

· Determination of the goals of system analysis;

· Formation of criteria;

· Generation of alternatives;

· Implementation of choice and decision making;

· Implementation of the analysis results.

4. Defining the goals of systems analysis

4.1 Fproblem formulation

For traditional sciences, the initial stage of work is to formulate a formal problem to 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 defining goals in systems analysis is related to problem formulation. The following feature of the system analysis tasks should be noted here. 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 systems analyst should 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 purpose of the system analysis is formulated is not isolated. It is connected with other systems, it is part of a certain supersystem, for example, an automated control system for a department or shop at an enterprise is a structural unit of the automated control system of the entire enterprise. Therefore, when formulating a problem for the system under consideration, it is necessary to take into account how the solution to 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 that contains this system. Thus, any real problem should be treated not as a single one, but as an object from a number of interrelated problems.

When formulating a system of problems, the systems analyst should follow some guidelines. First, the customer's opinion should be taken as a basis. As a rule, this is the head of the organization, for which the system analysis is carried out. It is he, as noted above, that generates the original formulation of the problem. Further, the systems analyst, having familiarized himself with the formulated problem, must understand the tasks that were assigned to the leader, the constraints and circumstances affecting the leader's behavior, the conflicting goals, between which he is trying to find a compromise. The systems analyst should study the organization for which the systems analysis is being conducted. It is necessary to be thoroughly familiar with the existing management hierarchy, the functions of the various groups, as well as previous research on related issues, if any. The analyst should refrain from expressing his preconceived opinion about the problem and from trying to squeeze 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 unverified the statements and comments of the manager. As already noted, the problem formulated by the leader must, firstly, be expanded to a complex of problems agreed with supra- and subsystems, and, secondly, it must be coordinated with all stakeholders.

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 or the other side wants to make. In addition, the problem must be considered comprehensively, including in a temporary, historical perspective. It is required to anticipate how the formulated problems may change over time or due to the fact that the research will interest 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 has been formulated, they proceed to defining the goal. Determining the purpose of the system analysis means answering the question of what needs to be done to solve the problem. To formulate a goal means to indicate the direction in which to move in order to solve an existing problem, to show the paths that lead away from the existing problem situation.

When formulating a goal, you must always be aware of the fact 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 the system analysis will determine the entire further complex of works. Therefore, the goals must be realistic. Setting realistic goals will direct all the activities of performing 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 the ideas about it develop, the goal can be reformulated. Changes in goals over time can occur not only in form, due to an ever 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 changes in ideas about goals, aging goals are different and depend on the level of the hierarchy of the object's consideration. Higher tier targets are more durable. The dynamism of goals should be taken into account in the systems analysis.

When formulating a 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 factors that objectively influence the process of goal formation as external ones.

Further, it should be noted that even at the very upper level the hierarchy of the system has a plurality of goals. When analyzing a problem, it is necessary to take into account the goals of all stakeholders. Among the many goals, it is desirable to try to find or form a global goal. If this cannot be done, the goals should be ranked in the order of their preference to solve the problem in the analyzed system.

The study of the goals of stakeholders in the problem should provide for the possibility of their clarification, expansion or even replacement. This circumstance is the main reason for the iterative system analysis.

The choice of the subject's goals is decisively influenced by the value system that he adheres to, therefore, when forming goals, a necessary stage of work is to identify the value system that the decision-maker adheres to. So, for example, distinguish 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 wait for 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 should live in harmony with nature, etc. The practice of human society development shows that following a 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 development goals of the system, taking into account both value systems.

5. Generating alternatives

The next stage of the 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 carried out. This stage of the system analysis is very important and difficult. Its importance lies in the fact that the ultimate goal of systems analysis is to choose the best alternative on a given set and to justify this choice. If the best one did not get into the formed set of alternatives, then none of the most perfect methods of analysis will help to calculate it. The difficulty of this stage is due to the need to generate a sufficiently complete set of alternatives, including, at first glance, even the most unrealizable ones.

Generating alternatives, i.e. ideas about possible ways to achieve a goal is a real creative process. There are a number of recommendations on possible approaches to performing this procedure. It is necessary to generate as many alternatives as possible. The following generation methods are available:

a) search for alternatives in patent and journal literature;

b) involving several experts with different backgrounds 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 that are opposite to those proposed, including the “zero” alternative (do nothing, ie consider the consequences of developments without the intervention of systems technicians);

f) stakeholder interviews and broader questionnaires; g) including into consideration even those alternatives that at first glance seem far-fetched;

g) generating alternatives designed 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 given view activities. Are of great importance psychological factors affecting the intensity of creative activity, therefore, 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 many alternatives, which must be mentioned. If you specifically strive to ensure that on initial stage as many alternatives as possible were obtained, i.e. try to make the set of alternatives as complete as possible, then for some problems their number can reach many tens. For a detailed study of each of them, an unacceptably large investment of time and money will be required. Therefore, in this case, it is necessary to conduct a preliminary analysis of the alternatives and try to narrow the set at the early stages of the analysis. At this stage of the analysis, qualitative methods are used to compare alternatives, without resorting to more accurate quantitative methods. Thereby, rough screening is carried out.

Let us now give the methods used in systems analysis to carry out work on the formation of a variety of alternatives.

6. Implementation of analysis results

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

The end 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 recommendations are implemented.

Currently, increased attention is paid to the implementation of the results of system analysis into practice. In this direction, the work of R. Ackoff can be noted. It should be noted that the practice of systems research and the practice of implementing their results differ significantly for systems of different types. According to the classification, systems are divided into three types: natural, artificial and socio-technical. 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 of human activity. Examples include all kinds of technical systems... In systems of the third type, in addition to natural connections, interpersonal connections play an important role. Such connections are due not to the natural properties of objects, but to cultural traditions, the upbringing of the subjects participating in the system, their character and other features.

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

When introducing 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. 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 systems research, it is necessary to ensure the improvement of the customer's organization from the point of view of at least one of the interested parties; at the same time, the 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 introduced into practice, is extremely rare, only in those cases when it comes to simple systems... In the study of socio-technical systems, they change over time, both in 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, and the relationship between stakeholders change. In addition, it should be noted that the implementation of the decisions made affects all factors of the functioning of the system. The stages of research and implementation in this type of systems actually merge, i.e. an iterative process is in progress. The conducted research has an impact on the life of the system, and this modifies the problem situation, sets a new research task. New problem situation stimulates further system analysis, etc. Thus, the problem is gradually solved through active research.

Vconclusion

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

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Principles and methods of system analysis. Expansion of the problem to the problematics, t

2. Application of system analysis

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