Methods of system analysis approaches. "Systems Theory and System Analysis
Any scientific, research and practical activity is carried out on the basis of methods, techniques and methodologies.
Method It is a method or way of doing things.
Methodology- a set of methods, techniques for carrying out any work.
Methodology- this is a set of methods, rules for the distribution and assignment of methods, as well as work steps and their sequence.
System analysis also has its own methods, techniques and methodologies. However, unlike the classical sciences, system analysis is in the development stage and does not yet have a well-established, generally recognized "toolkit".
In addition, each science has its own methodology, so let's give one more definition.
Methodology- a set of methods used in any science.
In a sense, we can also talk about the methodology of system analysis, although it is still a very loose, "raw" methodology.
1. Consistency
Before considering the system methodology, it is necessary to understand the concept of "system". Today, concepts such as "system analysis", " systems approach”, “system theory”, “systematic principle”, etc. However, they are not always distinguished and are often used as synonyms.
Most general concept, which denotes all possible manifestations of systems, is "systematic". Yu.P. Surmin proposes to consider the structure of systemicity in three aspects (Fig. 1): system theory, system approach and system method.
Rice. 1. The structure of consistency and its constituent functions.
1. System theory (system theory) implements explanatory and systematizing functions: gives rigorous scientific knowledge about the world of systems; explains the origin, structure, functioning and development of systems of various nature.
2. A systematic approach should be considered as a certain methodological approach of a person to reality, which is a certain commonality of principles, a systematic worldview.
An approach is a set of techniques, ways of influencing someone, in studying something, doing business, etc.
Principle - a) the basic, initial position of any theory; b) the most general rule of activity, which ensures its correctness, but does not guarantee unambiguity and success.
So, an approach is some generalized system of ideas about how this or that activity should be performed (but not a detailed algorithm of action), and the principle of activity is a set of some generalized techniques and rules.
Briefly, the essence of the system approach can be defined as follows:
A systematic approach is a methodology of scientific knowledge and practical activity, as well as an explanatory principle, which are based on the consideration of an object as a system.
The systematic approach consists in the rejection of one-sided analytical, linear-causal research methods. The main emphasis in its application is on the analysis of the integral properties of the object, the identification of its various connections and structure, features of functioning and development. The systems approach seems to be a fairly universal approach in the analysis, research, design and management of any complex technical, economic, social, environmental, political, biological and other systems.
The purpose of a systematic approach is that it directs a person to a systematic vision of reality. It forces us to consider the world from a systemic standpoint, more precisely, from the standpoint of its systemic structure.
Thus, the systematic approach, being the principle of cognition, performs orientational and worldview functions, providing not only a vision of the world, but also orientation in it.
3. The system method implements cognitive and methodological functions. It acts as some integral set of relatively simple methods and techniques of cognition, as well as the transformation of reality.
The ultimate goal of any system activity is to develop solutions, both at the design stage of systems and in their management. In this context, systems analysis can be considered a fusion of methodology general theory systems, a systematic approach and systematic methods of substantiation and decision-making.
2. Natural science methodology and systematic approach
System analysis is not something fundamentally new in the study of the surrounding world and its problems - it is based on a natural-science approach, the roots of which go back to past centuries.
The central place in the study is occupied by two opposite approaches: analysis and synthesis.
Analysis involves the process of dividing the whole into parts. It is very useful if you need to find out what parts (elements, subsystems) the system consists of. Knowledge is acquired through analysis. However, it is impossible to understand the properties of the system as a whole.
The task of synthesis is the construction of a whole from parts. Understanding is achieved through synthesis.
In the study of any problem, several main stages can be indicated:
1) setting the goal of the study;
2) highlighting the problem (singling out the system): highlight the main, essential, discarding the insignificant, insignificant;
3) description: to express in a single language (level of formalization) phenomena and factors that are heterogeneous in nature;
4) establishing criteria: to determine what is "good" and "bad" for evaluating the information received and comparing alternatives;
5) idealization (conceptual modeling): introduce a rational idealization of the problem, simplify it to an acceptable limit;
6) decomposition (analysis): divide the whole into parts without losing the properties of the whole;
7) composition (synthesis): combine parts into a whole without losing the properties of the parts;
8) solution: find a solution to the problem.
In contrast to the traditional approach, in which the problem is solved in a strict sequence of the above stages (or in a different order), the system approach consists in the multiple connection of the solution process: the stages are considered together, in interconnection and dialectical unity. In this case, a transition to any stage is possible, including a return to setting the goal of the study.
The main feature of a systematic approach is the presence of a dominant role of a complex, not simple, whole, and not constituent elements. If, in the traditional approach to research, thought moves from the simple to the complex, from parts to the whole, from elements to the system, then in the systems approach, on the contrary, thought moves from the complex to the simple, from the whole to constituent parts, from system to elements. At the same time, the effectiveness of a systematic approach is the higher, the more complex it is applied to.
3. System activity
Whenever the question of system analysis technologies is raised, insurmountable difficulties immediately arise due to the fact that there are no established systems analysis technologies in practice. System analysis is currently a loosely coupled set of techniques and methods of an informal and formal nature. So far, intuition dominates in systems thinking.
The situation is aggravated by the fact that, despite the half-century history of the development of system ideas, there is no unambiguous understanding of the system analysis itself. Yu.P. Surmin identifies the following options for understanding the essence of system analysis:
Identification of the technology of system analysis with the technology of scientific research. At the same time, there is practically no place for the system analysis itself in this technology.
Reduction of system analysis to system design. In fact, system-analytical activity is identified with system-technical activity.
A very narrow understanding of system analysis, reducing it to one of its components, for example, to structural-functional analysis.
Identification of system analysis with a systematic approach to analytical activity.
Understanding system analysis as a study of system patterns.
In a narrow sense, system analysis is quite often understood as a set of mathematical methods for studying systems.
Reducing system analysis to a set of methodological tools that are used to prepare, justify and implement solutions to complex problems.
Thus, what is called system analysis is an insufficiently integrated array of methods and techniques of system activity.
Today, the mention of system analysis can be found in many works related to management and problem solving. And although it is quite rightly considered as an effective method for studying management objects and processes, there are practically no methods of system analytics in solving specific management problems. As Yu.P. Surmin: "System analysis in management is not a developed practice, but growing mental declarations that do not have any serious technological support."
4. Approaches to the analysis and design of systems
When analyzing and designing existing systems, various specialists may be interested in different aspects: from the internal structure of the system to the organization of control in it. In this regard, the following approaches to analysis and design are conventionally distinguished: 1) system-element, 2) system-structural, 3) system-functional, 4) system-genetic, 5) system-communicative, 6) system-management and 7 ) system-information.
1. System-element approach. The indispensable property of systems is their components, parts, exactly what the whole is formed from and without which it is impossible.
The system-element approach answers the question of what (what elements) the system is formed from.
This approach was sometimes referred to as "enumerating" the system. At first, they tried to apply it to the study of complex systems. However, the very first attempts to apply this approach to the study of management systems of enterprises and organizations showed that it is almost impossible to “list” a complex system.
Example. There was such a case in the history of the development of automated control systems. The developers wrote dozens of volumes of the system survey, but could not start creating the ACS, because they could not guarantee the completeness of the description. The development manager was forced to quit, and subsequently began to study the systematic approach and popularize it.
2. System-structural approach. The components of the system are not a collection of random incoherent objects. They are integrated by the system, they are components of this particular system.
The system-structural approach is aimed at identifying the component composition of the system and the links between them that ensure purposeful functioning.
In a structural study, the subject of research, as a rule, is the composition, structure, configuration, topology, etc.
3. System-functional approach. The goal acts in the system as one of the important system-forming factors. But the goal requires actions aimed at achieving it, which are nothing but its functions. Functions in relation to the goal act as ways to achieve it.
The system-functional approach is aimed at considering the system from the point of view of its behavior in the environment in order to achieve goals.
In a functional study, the following are considered: dynamic characteristics, stability, survivability, efficiency, i.e., everything that, with an unchanged structure of the system, depends on the properties of its elements and their relationships.
4. Systemic genetic approach. Any system is not immutable, once and for all given. It is not absolute, not eternal, mainly because it has internal contradictions. Each system not only functions, but also moves, develops; it has its beginning, is experiencing the time of its birth and formation, development and flourishing, decline and death. And this means that time is an indispensable attribute of the system, that any system is historical.
The system-genetic (or system-historical) approach is aimed at studying the system from the point of view of its development in time.
The system-genetic approach determines the genesis - the emergence, origin and formation of an object as a system.
5. System-communicative approach. Each system is always an element (subsystem) of another, more high level, system, and itself, in turn, is formed from subsystems of a lower level. In other words, the system is connected by many relationships (communications) with a variety of systemic and non-systemic formations.
The system-communicative approach is aimed at studying the system from the point of view of its relations with other systems external to it.
6. System management approach. The system constantly experiences perturbing influences. These are, first of all, internal perturbations, which are the result of the internal inconsistency of any system. These include external perturbations, which are far from always favorable: lack of resources, severe restrictions, etc. Meanwhile, the system lives, functions, and develops. So, along with a specific set of components, internal organization(structure), etc., there are other system-forming, system-preserving factors. These factors to ensure the stability of the system are called management.
The system management approach is aimed at studying the system from the point of view of providing
baking its purposeful functioning in the conditions of internal and external disturbances.
7. System-information approach. Management in the system is unthinkable without the transmission, receipt, storage and processing of information. Information is a way of connecting the components of the system with each other, each of the components with the system as a whole, and the system as a whole with the environment. In view of the foregoing, it is impossible to reveal the essence of systemicity without studying its informational aspect.
The system-information approach is aimed at studying the system from the point of view of transmitting, receiving, storing and processing data within the system and in connection with the environment.
5. Methods of system analysis
The methodology of system analysis is a rather complex and variegated set of principles, approaches, concepts and specific methods, as well as techniques.
The most important part of the methodology of system analysis is its methods and techniques (for simplicity, in what follows, we will generally talk about techniques).
5.1. Overview of systems analysis techniques
The available methods of system analysis have not yet received a sufficiently convincing classification that would be unanimously accepted by all experts. For example, Yu. I. Chernyak divides the methods of systematic research into four groups: informal, graphic, quantitative, and modeling. A rather deep analysis of the methods of various authors is presented in the works of V.N. Volkova, as well as Yu.P. Surmina.
The following sequence can be considered as the simplest version of the system analysis methodology:
1) statement of the problem;
2) structuring the system;
3) building a model;
4) study of the model.
Other examples and analysis of the stages of the first methods of system analysis are given in the book, which discusses the methods of leading experts in system analysis of the 70s and 80s of the last century: S. Optner, E. Quaid, S. Young, E.P. Golubkov. Yu.N. Chernyak.
Examples: Stages of system analysis methods according to S. Optner:
1. Identification of symptoms.
2. Determining the relevance of the problem.
3. Definition of the goal.
4. Opening the structure of the system and its defective elements.
5. Determination of the structure of opportunities.
6. Finding alternatives.
7. Evaluation of alternatives.
8. Choice of an alternative.
9. Drawing up a decision.
10. Recognition of the decision by the team of performers and leaders.
11. Starting the solution implementation process
12. Management of the solution implementation process.
13. Evaluation of implementation and its consequences.
Stages of system analysis techniques according to S. Yang:
1. Determining the purpose of the system.
2. Identification of problems of the organization.
3. Investigation of problems and diagnosis
4. Search for a solution to the problem.
5. Evaluation of all alternatives and selection of the best one.
6. Coordination of decisions in the organization.
7 Approval of the decision.
8. Preparation for input.
9. Managing the application of the solution.
10. Checking the effectiveness of the solution.
Stages of system analysis methods according to Yu.I. Chernyak:
1. Analysis of the problem.
2. System definition.
3. Analysis of the structure of the system.
4. Formation of a common goal and criterion.
5. Decomposition of the goal and identification of the need for resources and processes.
6. Identification of resources and processes - composition of goals.
7. Forecast and analysis of future conditions.
8. Evaluation of ends and means.
9. Selection of options.
10. Diagnosis of the existing system.
11. Construction integrated program development.
12. Designing an organization to achieve goals.
From the analysis and comparison of these methods, it can be seen that the following stages are presented in them in one form or another:
identifying problems and setting goals;
development of options and decision-making models;
evaluation of alternatives and search for a solution;
solution implementation.
In addition, in some methods there are stages for evaluating the effectiveness of solutions. In the most complete methodology, Yu.I. Chernyak specifically provides for the stage of designing an organization to achieve the goal.
At the same time, various authors focus their attention on different stages, respectively, detailing them in more detail. In particular, the focus is on the following steps:
development and research of decision-making alternatives (S. Optner, E. Quaid), decision-making (S. Optner);
substantiation of the goal and criteria, structuring the goal (Yu.I. Chernyak, S. Optner, S. Yang);
managing the process of implementing an already adopted decision (S. Optner, S. Yang).
Since the execution of individual stages can take quite a lot of time, there is a need for greater detail, division into sub-stages and a clearer definition of the final results of the sub-stages. In particular, in the method of Yu.I. Chernyak, each of the 12 stages is divided into sub-stages, of which there are a total of 72.
Other authors of system analysis methods include E.A. Kapitonov and Yu.M. Plotnitsky.
Examples: E.A. Kapitonov identifies the following successive stages of system analysis.
1. Setting goals and main objectives of the study.
2. Determining the boundaries of the system in order to separate the object from the external environment, to distinguish between its internal and external relations.
3. Revealing the essence of integrity.
A similar approach is also used by Yu. M. Plotnitsky, who considers system analysis as a set of steps to implement the system approach methodology in order to obtain information about the system. He distinguishes 11 stages in the system analysis.
1. Formulation of the main goals and objectives of the study.
2. Determining the boundaries of the system, separating it from the external environment.
3. . Compilation of a list of system elements (subsystems, factors, variables, etc.).
4. Identification of the essence of the integrity of the system.
5. Analysis of interrelated elements of the system.
6. Building the structure of the system.
7. Establishing the functions of the system and its subsystems.
8. Coordination of the goals of the system and each subsystem.
9. Clarification of the boundaries of the system and each subsystem.
10. Analysis of emergence phenomena.
11. Designing a system model.
5.2. Development of system analysis methods
The ultimate goal of system analysis is to assist in understanding and solving an existing problem, which boils down to finding and choosing a solution to the problem. The result will be the selected alternative either in the form of a management decision or in the form of the creation new system(in particular, management systems) or reorganization of the old one, which again is a management decision.
Incompleteness of information about problem situation complicates the choice of methods for its formalized representation and does not allow the formation of a mathematical model. In this case, there is a need to develop methods for conducting system analysis.
It is necessary to determine the sequence of stages of system analysis, recommend methods for performing these stages, and provide for a return to previous stages if necessary. Such a sequence of stages and sub-stages, identified and ordered in a certain way, in combination with the recommended methods and techniques for their implementation, constitutes the structure of the system analysis methodology.
Practitioners see methodologies as an important tool for solving problems in their subject area. And although today a large arsenal of them has been accumulated, but, unfortunately, it should be recognized that the development of universal methods and techniques is not possible. In each subject area, for various types of problems being solved, a systems analyst has to develop his own system analysis methodology based on a variety of principles, ideas, hypotheses, methods and techniques accumulated in the field of systems theory and system analysis.
The authors of the book recommend that when developing a methodology for system analysis, first of all, determine the type of task (problem) being solved. Then, if the problem covers several areas: the choice of goals, the improvement of the organizational structure, the organization of the decision-making and implementation process, highlight these tasks in it and develop methods for each of them.
5.3. An example of an enterprise system analysis methodology
As an example of a modern methodology for system analysis, let's consider a certain generalized methodology for analyzing an enterprise.
The following list of system analysis procedures is proposed, which can be recommended to managers and specialists in economic information systems.
1. Determine the boundaries of the system under study (see the selection of a system from environment).
2. Determine all subsystems that include the system under study as a part.
If the impact on the enterprise of the economic environment is clarified, it will be the supersystem in which its functions should be considered (see hierarchy). Based on the interconnectedness of all spheres of life modern society, any object, in particular, an enterprise, should be studied as an integral part of many systems - economic, political, state, regional, social, environmental, international. Each of these supersystems, for example, the economic one, in turn, has many components with which the enterprise is connected: suppliers, consumers, competitors, partners, banks, etc. These components are simultaneously included in other supersystems - sociocultural, environmental, etc. And if we also take into account that each of these systems, as well as each of their components, have their own specific goals that contradict each other, then the need for a conscious study of the environment surrounding the enterprise becomes clear (see expanding the problem to a problematic). Otherwise, the whole set of numerous influences exerted by supersystems on the enterprise will seem chaotic and unpredictable, excluding the possibility of reasonable management of it.
3. Determine the main features and directions of development of all supersystems to which this system belongs, in particular, formulate their goals and contradictions between them.
4. Determine the role of the system under study in each supersystem, considering this role as a means of achieving the goals of the supersystem.
Two aspects should be considered in this regard:
the idealized, expected role of the system from the point of view of the supersystem, i.e., those functions that should be performed in order to realize the goals of the supersystem;
the real role of the system in achieving the goals of the supersystem.
For example, on the one hand, an assessment of the needs of buyers in a particular type of goods, their quality and quantity, and on the other hand, an assessment of the parameters of goods actually produced by a particular enterprise.
Determining the expected role of the enterprise in the consumer environment and its real role, as well as comparing them, makes it possible to understand many of the reasons for the success or failure of the company, the features of its work, and to foresee the real features of its future development.
5. Identify the composition of the system, i.e., determine the parts of which it consists.
6. Determine the structure of the system, which is a set of links between its components.
7. Determine the functions of the active elements of the system, their "contribution" to the implementation of the role of the system as a whole.
Of fundamental importance is the harmonic, consistent combination of the functions of different elements of the system. This problem is especially relevant for departments, workshops large enterprises, whose functions are often in many ways "not docked", are not sufficiently subordinated to the general plan.
8. Reveal the reasons that unite individual parts into a system, into integrity.
They are called integrating factors, which primarily include human activity. In the course of activity, a person realizes his interests, defines goals, carries out practical actions, forming a system of means to achieve goals. The initial, primary integrating factor is the goal.
The goal in any field of activity is a complex combination of various conflicting interests. The true goal lies in the intersection of such interests, in their peculiar combination. Comprehensive knowledge of it allows us to judge the degree of stability of the system, its consistency, integrity, to foresee the nature of its further development.
9. Determine all possible connections, communications of the system with the external environment.
For a really deep, comprehensive study of the system, it is not enough to reveal its connections with all the subsystems to which it belongs. It is also necessary to know such systems in the external environment, to which the components of the system under study belong. Thus, it is necessary to define all the systems to which the employees of the enterprise belong - trade unions, political parties, families, systems of socio-cultural values and ethical norms, ethnic groups, etc. It is also necessary to know the connections well structural divisions and employees of the enterprise with systems of interests and goals of consumers, competitors, suppliers, foreign partners, etc. It is also necessary to see the connection between the technologies used at the enterprise and the “space” of the scientific and technical process, etc. Awareness of the organic, albeit contradictory, unity of all systems surrounding the enterprise allows us to understand the reasons for its integrity, to prevent processes leading to disintegration.
10. Consider the system under study in dynamics, in development.
For a deep understanding of any system, one cannot limit oneself to considering short periods of time of its existence and development. It is advisable, if possible, to investigate its entire history, to identify the reasons that prompted the creation of this system, to identify other systems from which it grew and was built. It is also important to study not only the history of the system or its dynamics current state, but also try, using special techniques, to see the development of the system in the future, i.e., to predict its future states, problems, opportunities.
The need for a dynamic approach to the study of systems can be easily illustrated by comparing two enterprises that at some point in time had the same values of one of the parameters, for example, sales volume. From this coincidence it does not follow at all that enterprises occupy the same position in the market: one of them can gain strength, move towards prosperity, and the other, on the contrary, experience a decline. Therefore, it is impossible to judge any system, in particular, about an enterprise, only by a “snapshot” of one value of any parameter; it is necessary to investigate changes in parameters by considering them in dynamics.
The sequence of procedures for system analysis outlined here is not mandatory and regular. The list of procedures is mandatory rather than their sequence. The only rule is that it is expedient to repeatedly return during the study to each of the described procedures. Only this is the key to a deep and comprehensive study of any system.
Summary
1. Any scientific, research and practical activity is carried out on the basis of methods (methods or methods of action), techniques (a set of methods and techniques for carrying out any work) and methodologies (a set of methods, rules for the distribution and assignment of methods, as well as work steps and their sequences).
2. The most general concept, which refers to all possible manifestations of systems, is "systematic", which is proposed to be considered in three aspects:
a) systems theory provides rigorous scientific knowledge about the world of systems and explains the origin, structure, functioning and development of systems of various nature;
b) a systematic approach - performs orientation and worldview functions, provides not only a vision of the world, but also orientation in it;
c) system method - implements cognitive and methodological functions.
3. System analysis is not something fundamentally new in the study of the surrounding world and its problems - it is based on a natural science approach. In contrast to the traditional approach, in which the problem is solved in a strict sequence of the above steps (or in a different order), the systems approach consists in the multiple-connectedness of the solution process.
4. The main feature of a systematic approach is the presence of a dominant role of a complex, not simple, whole, and not constituent elements. If, with the traditional approach to research, thought moves from the simple to the complex, from parts to the whole, from elements to the system, then with the systematic approach, on the contrary, thought moves from the complex to the simple, from the whole to its constituent parts, from the system to the elements. .
5. When analyzing and designing existing systems, various specialists may be interested in different aspects - from the internal structure of the system to the organization of management in it, which gives rise to the following approaches to analysis and design; system-element, system-structural, system-functional, system-genetic, system-communicative, system-management and system-information.
6. The methodology of system analysis is a set of principles, approaches, concepts and specific methods, as well as techniques.
Methodology is a system of principles and methods for organizing and building theoretical and practical activities. If the theory is the result of the process of cognition, then the methodology is the rationale for the way to achieve and build the knowledge obtained on its basis. Methodology provides a philosophical justification for the methods and techniques of organizing the entire diversity of species (including cognitive) human activity and involves the development of methods adequate to the studied and transformed objects. One of the most important functions of methodology is heuristic: it must not only describe and explain some subject area, but at the same time be a tool for the search for new knowledge.
To put it briefly, methodology is the doctrine of method.
For social sciences can be identified three levels of methodology:
- general scientific (for example, a systematic approach);
- general social ( social philosophy);
- private social (sociology of personality, labor, youth
Method - a set of techniques and operations of theoretical and practical development of reality. For the field of social research, this is the main way to collect, process and analyze empirical materials.
Methodology - a set of technical techniques due to this method, including private operations, their sequence and interconnection.
AT modern science and social practice as a general scientific methodology, designed to formulate in a complete form a fairly universal set of research methods, as well as techniques and rules of constructive activity for subject areas of very different types and classes, is systems approach. The systems approach is based on principle of consistency, according to which the complex phenomena of objective reality are considered as integral phenomena formed by special mechanisms of communication and functioning of their constituent parts. On this basis, a specialized cognitive apparatus is formed, which determines the way of seeing the real world.
As you know, a system is such a set of interrelated elements, the interaction of which gives rise to a special system quality, quite clearly localizing this set in the space surrounding it. It should be noted that the elements forming the system are attached to the specified system quality only as part of this system.
The system is always in a state of interaction with the external environment, which for it is, on the one hand, a source of resources necessary for its life, on the other hand, a source of various kinds of disturbing influences that can be useful (and then they are assimilated by the system), neutral (the system of their simply ignores) or harmful (the system tries to dampen their negative impact with the help and within the available resources).
Systematic consideration of an object involves:
- definition and study of systemic quality;
- identification of the totality of elements forming the system;
- establishing links between these elements;
- study of the properties of the environment surrounding the system, important for
the functioning of the system, at the macro and micro levels;
Revealing the relationships connecting the system with the environment.
The development of science and management practice also shows that a systematic approach to the study of a complex society makes it possible to comprehensively study the structural units of society (classes, layers, groups, associations, personalities), social relations between them (contacts, actions, interactions, social relations, social institutions), as well as the dynamics of social structures (social changes, processes).
The main advantage of the systematic approach is that it requires the maximum possible consideration of all aspects of the problem in their relationship and integrity, highlighting the main and essential, determining the nature and direction of the links between the structural components of the problem.
System analysis in a narrow sense, is a set of scientific methods and practices, which can be used in the study and / or development of complex and super-complex objects, as well as in solving various problems that arise in all areas of managing social and organizational and technological systems. In a broad sense, systems analysis is understood as a synonym for a systems approach.
The scientific apparatus and methodological arsenal of system analysis were generally formed in the United States in the early 1940s. 20th century in the search for new approaches to solving the very complicated problems of production and rapid improvement of new types of weapons. It was noted that the main issue in solving any problems - regardless of their area, content and nature - is the choice of the most optimal solution alternative. However, this choice depends on the ability to evaluate the effectiveness of each alternative and the costs required for its implementation. Such operations were mastered by the investment of capital and the development of industry even before the Second World War. For their implementation, a number of methods were proposed, which, despite the constructiveness of the results in these areas, were almost never used in the field of armaments. Work on the creation of weapons systems began without considering how they would be used, how much they would cost, and whether their use would justify the costs of development and creation. The reason for this situation was that at that time the relative costs of armaments were low, there were few options for choice, so the principle of "nothing but the best" was actually used. During the Second World War, and especially with the beginning of the "atomic age", the cost of creating weapons increased many times over, and this approach became unacceptable. It was gradually replaced by another: "only what is needed, and at the minimum cost."
To implement this principle, it was necessary to be able to find, evaluate and compare simultaneously many alternatives for the production of weapons of various types. Operations research models developed by this time in industry and commerce could not be used for this because of their inherent limitations. New methods were required to be able to consider many alternatives, each of which was described by a large number of variables as a whole, while ensuring the completeness of the assessment of each alternative and the level of its uncertainty. The resulting universal problem-solving methodology was named by its authors "system analysis". The new methodology created to solve military problems was primarily used in this area. However, it soon became clear that civil, financial and many other problems of firms not only allow, but also require the use of this methodology.
Systems analysis quickly absorbed the achievements of many related and related fields and different approaches and turned into an independent, rich in forms and areas of application, unique in its purpose and nature of scientific and applied discipline and area of professional activity.
Initial theoretical basis for systems analysis is systems theory and systems approach. However, systems analysis borrows from them only the most general concepts and premises. In contrast, for example, to the systems approach, system analysis has a developed methodological and instrumental apparatus of its own and borrowed from other areas of science.
System analysis is based on strict adherence to the following principles:
- the decision-making process should begin with a justification and a clear formulation of the final goals;
- any problem should be presented as an integral unified system, indicating the relationships and consequences of each particular decision;
- the solution of the problem should be represented by a set of possible alternative ways to achieve the goal;
- the goals of individual units should not contradict the goals of the entire system as a whole.
The system analysis algorithm is based on the construction of a generalized model that reflects all the factors and relationships of the problem situation that may appear in the solution process. The system analysis procedure consists in checking the consequences of each of the possible alternative solutions for choosing the optimal one according to any criterion or their combination.
The specificity of system analysis is an orientation towards finding optimal solutions with limited resources (personnel, finance, time, technology, etc.). It begins at the stage of the management cycle, when the goals of management are determined and ordered while finding a correspondence between the goals, possible ways to achieve them, the necessary and available resources for this.
In the center system analysis methodologies the operation of a quantitative comparison of alternatives is found, which is performed in order to select the optimal (according to certain criteria) alternative, which is supposed to be implemented. This can be achieved if all elements of the alternative are taken into account and the correct estimates are given to each of them. Thus, the idea arises of highlighting all the elements associated with a given alternative, i.e., "comprehensive consideration of all circumstances." The resulting integrity is called in system analysis complete system or simply system. The only criterion that makes it possible to single out this system can only be the fact of participation of this element in the process leading to the appearance of a given (target, desired) output result for a given alternative. Thus the concept process turns out to be central in the methodology of system analysis. There can be no systems thinking without a clear understanding of the process.
To define a system means to define system objects, their properties and relationships. The most important of these are input, process, output, feedback, and constraint.
System input called something that changes with the flow this process. Or otherwise, this is what this process must be applied to in order to obtain the desired result. In many cases, the components of an input are a "working input" (what is being "processed") and a processor (what is being "processed"). System output called the result or final state of the process. The process translates an input into an output. The ability to transform an input into a specific output is called property of a given process or transfer function (IV).
Here it is necessary to pay attention to the fact that in the social world processes do not always translate "input" into definite"exit" because social structures are not at all like those “devices” that are considered in classical system models. Unlike the latter, which work out input signals on rigid (or non-rigid, but quite predictable, probabilistic) algorithms social structures, being predominantly self-organizing systems, only perceive management influences. But far from passive and highly subjective. For this reason, they cannot be displayed in formal constructions using fixed transfer functions that indicate the nature of the transformation of "input" into "output". social facilities are constantly changing, in the most bizarre way perceiving and associating all any significant phenomena of the internal and external order.
In any functioning system, there are three sub-processes of different roles: the main process, feedback and restriction. The main process converts input to output. Feedback performs a number of operations: compares the real state of the output with a given (target) model and highlights the difference (A). The subsequent analysis of the content and meaning of the difference makes it possible to develop, if necessary, a managerial decision. The need for a decision arises when the difference in the state of input and output exceeds some set or accepted level, that is, when a problem arises for which a decision must be made. The meaning of this solution lies in such a correction of the system process, the implementation of which could bring the real state of the system output closer to its model or bring their difference to an acceptable level.
Limitation there is a sum of rules, regulations, and guidelines put forward personally or from outside, defining the boundary of the problem. It is formed by the consumer (buyer) of the system output. In a generalized form, the constraint can be viewed as external environment generally. The system constraint is taken into account when making a management decision, ensuring that the system output matches the consumer's goals. Thus, the constraint of the system is reflected in the adjusted output model.
The functioning system is shown in fig. 2.1. A circle with an oblique cross denotes a comparison unit (comparator, adder), in which all the most important controlled parameters are compared.
Rice. 2.1.
In systems analysis, it is postulated that every system consists of subsystems and every system is a subsystem of some other system more than high order. It is also postulated that any system can be described in terms of system objects, properties and relationships. The system boundary is determined by a set of inputs from the external environment. The external environment is a set of systems for which this system is not a functional subsystem.
problem called a situation characterized by a difference between the necessary (desired) and the existing outputs. The latter is necessary if its absence creates a threat to the existence or development of the system. It is provided by the existing system. The desired output is provided by the desired system. The problem is the difference between the existing and desired systems. The problem may be to prevent a decrease or to increase the output. The problem condition represents the existing system (the "known"). The requirement represents the desired system. Solution there is something that fills the gap between the existing and the desired systems. The system that fills the gap is the object of construction.
Problems can manifest themselves in symptoms. Systematically manifested symptoms form trend. Finding a problem is the result of a process of identifying symptoms. Identification is possible under the condition of knowledge of the norm or the desired behavior of the system. The detection of a problem is followed by the prediction of its development and the assessment of the relevance of its solution, i.e., the state of the system with an unresolved problem. Assessment of the relevance of solving the problem allows you to determine the need for its solution.
The process of finding a solution centers around the iteratively performed operations of identifying the condition, goal, and possibilities for solving the problem. The result of identification is a description of the condition, purpose and capabilities in terms of system objects (input, process, output, feedback and limitation), properties and relationships. If the structures and elements of the conditions, goals and possibilities of this problem are known, identification has the character of determining quantitative relationships, and the problem is called quantitative. If the structure and elements of the conditions, goals and opportunities are known in part, the identification is of a qualitative nature, and the problem is called qualitative or semi-structured. As a problem-solving methodology, systems analysis indicates a fundamentally necessary sequence of interrelated operations, which (in the most general terms) consists of identifying a problem, constructing a solution to the problem, and implementing this solution. The decision process is the design, evaluation and selection of system alternatives according to the criteria of cost, time, efficiency and risk, taking into account the relationship between the marginal increments of these quantities (marginal ratios). The choice of the boundaries of this process is determined by the condition, purpose and possibilities of its implementation. The most adequate construction of this process involves the comprehensive use of heuristic conclusions within the framework of the postulated structure of the system methodology.
The reduction of the number of variables is carried out on the basis of an analysis of the sensitivity of the problem to changes in individual variables or groups of variables, aggregation of variables into summary factors by selecting criteria of an appropriate form, and also using, where possible, mathematical methods for reducing enumeration (mathematical programming, etc.). The logical integrity of the process is provided by explicit or implicit assumptions, each of which can be a source of risk. It is postulated that the structure of system functions and problem solving is standard for any systems and any problems. Only the methods of implementing functions can change. The improvement of methods in a given state of scientific knowledge has a limit, defined as a potentially achievable level. As a result of solving the problem, new connections and relationships are established, some of which determine the desired outcome, and the other determines unforeseen opportunities and limitations that can become a source of future problems.
INTRODUCTION
System analysis is a scientific discipline that deals with solving problems related to the study of systems of various physical nature, purpose and scale, management of the evolution of systems, optimization of parameters, structure and algorithms for the functioning of systems, making optimal decisions on the organization and development of systems. Therefore, the origins of systems analysis and its methodology lie in systems theory, operations research theory, decision theory, and control theory.
The emergence of the discipline "system analysis" is due to the need to conduct research on systems of an interdisciplinary nature. Creation, operation and development of complex technical systems, design and management of large-scale energy, transport, production systems, analysis ecological systems and systems of social purpose and many other areas of practical and scientific activity demanded the organization of research that would be of an unconventional nature.
On the present stage development of system analysis, its apparatus and tools are based on the widespread use of computers and include a complex and developed system of models. The development of system analysis was determined, on the one hand, by the development of the mathematical apparatus and the development of formalization methods, and on the other hand, by new tasks that arise in industry, economics, military affairs, etc. System analysis includes both Scientific research systems, as well as relevant activities aimed at the practical implementation of the results of such studies.
The scientific discipline called systems analysis studies events and processes in systems, develops models designed to explain these events and processes, and uses these models to study changes in the evolution and characteristics of systems when its structural and functional parameters change. Thus, systems analysis is a science, since this discipline uses scientific method to obtain relevant knowledge and differs from other sciences by the subject of research. System analysis, like any other science, requires the development of its own mathematical apparatus of methods of system analysis, focused on the specifics inherent in this area and research objectives.
Distinctive features of system analysis are that it is based on the use of a modern scientific approach to the study and management of systems of various nature and purpose - the system principle, integrated research teams and the scientific method.
for solving problems of system analysis. The systems principle is the recognition that every system is made up of parts, each with its own evolutionary goals, and that in any system the evolution of each part affects all other parts of the system. The scientific method of system analysis, in particular, is based on the fact that, as a rule, the entire system that is the object of study cannot be subjected to a natural experiment. Therefore, in most cases, investigating the system
in In general, it is necessary to apply an approach that is not related to conducting full-scale experiments.
The concept of the systems principle has had a significant impact on the planning and executive functions of systems management. System administrators are increasingly turning to systems analysts for help in choosing from a variety of possible solutions. The value of the system principle for managing the system is determined by the content of the main goal of management. First, it is necessary to achieve the efficiency of the functioning of the system as a whole and not allow the interests of any one part of the system to interfere with the achievement of the overall goals of the creation and functioning of the system. Secondly, it is necessary to achieve this on the condition that the parts of the system have, as a rule, conflicting goals for their functioning. Thirdly, it is necessary to understand that it is possible to achieve the general goals of the functioning of the system only if it is considered as a whole, striving for this to understand and evaluate the interaction of all its parts and combine them on such a basis that would allow the system as a whole to effectively achieve her goal. Any formal analysis of the system, or even an attempt at a formal analysis, is usually valuable in that, at a minimum, it makes the system administrator think about the main thing and move
in direction. And although the system analyst in his conclusion will not always be able to accurately indicate to the administrator which solution would be the best, the very fact of the analysis will require him to list the alternatives and formulate the goals of the system analysis.
Without striving for an exhaustive formal definition of system analysis, we note that this science is mainly engaged in the analysis of organizational (functional) systems, i.e. systems whose work is determined by the decisions of people (as opposed to, for example, physical systems that obey only the laws of nature) . System analysis provides a mathematical description of the processes of functioning of systems and their management. It is focused on solving problems for which it is possible to build mathematical models of systems that allow obtaining optimal solutions. In any system analysis project, the following main stages can be distinguished: problem statement, development of a system model, finding a solution, checking the model and evaluating the solution, implementing the solution and monitoring its correctness. In sys-
dark analysis the main role assigned to mathematical modeling. To build a mathematical model, it is necessary to have a clear understanding of the purpose of the functioning of the system under study and to have information about the limitations that determine the area allowed values controlled variables. Analysis of the model should lead to the determination of the best impact on the object of study if all the established restrictions are met.
The complexity of real systems can make it very difficult to present the goal and constraints in an analytical way. Therefore, it is very important to reduce the "dimension" of the problem being solved in such a way as to ensure the possibility of constructing an appropriate model. Despite too big number variables and constraints that, at first glance, must be taken into account when analyzing real systems, only a small part of them turns out to be essential for describing the behavior of the systems under study. Therefore, in a simplified description of real systems, on the basis of which one or another model will be built, one should first of all identify the essential variables, parameters, and limitations.
When the term "systems analysis" is used, it almost always means the application of mathematical methods to model systems and analyze their characteristics. Indeed, mathematical models and methods occupy a central place in system analysis. However, it should be borne in mind that solving problems of organizational management does not always come down to building models and performing appropriate experiments with them. This is due, in particular, to the fact that in the course of the formation of control decisions one often encounters factors that are essential for the correct solution of the problem, but are not amenable to strict formalization and, therefore, cannot be directly introduced into the mathematical model. One of the hard-to-formalizable factors of this kind is the factor of human activity.
System analysis as a methodology for solving problems of research and management of systems can be considered both as a science and as an art. The scientific content of system analysis is provided by the effective use of mathematical models and methods in solving problems of research and control of systems. At the same time, the successful completion of all stages of the study, from its inception to the implementation of the solution obtained using the developed mathematical model, is largely determined by the creative abilities and intuition of the researchers.
PROBLEMS OF SYSTEM ANALYSIS
1.1. Systems and Models
A system is a set of objects together with relationships between objects and between their attributes.
This definition assumes that a system has properties, functions, and purposes that are distinct from those of its constituent objects, relationships, and attributes.
Objects are simply parts or components of a system. Most of the systems that surround or interest us are
from physical parts, however, abstract objects can also be included in systems: mathematical variables, equations, laws, etc.
Attributes are properties of objects.
Attitude is one of the forms of the universal interconnection of all objects, phenomena, processes in nature, society and thinking.
The relations of objects to each other are extremely diverse: cause and effect, part and whole, the relationship between parts within the whole, argument and function, etc. In mathematics and logic, such types of relations as “... more than ... ”, “... implies ...”, etc. Any set of objects has internal relations, because the distance between objects can always be taken as a relation. It is assumed that the relations considered in a certain context depend on the problem being solved, and on this basis, certain essential or interesting relations are included in the consideration and trivial or non-essential relations are excluded. The researcher who solves the problem decides for himself which relationships are significant and which are trivial.
System environment- a set of all objects whose attributes or relationships change affect the system, as well as those objects whose attributes or relationships between these objects change as a result of the system.
The above definition raises a natural question: when is an object considered to belong to the environment, and when does it belong to the system? If some object interacts with the system in the way specified in the definition, does this mean that it is part of the system? The answers to these questions are not obvious. In the famous
sense, the system, together with the environment, represents a set of objects that are of interest to the researcher in a particular problem. The division of this set into two sets - the system and the environment - can be done in different ways, and all of them are quite arbitrary. Ultimately, the solution to this problem depends on the goals of the one who considers a certain set of objects as a system.
The general problem of defining the environment of a given system is far from simple. In order to fully define the environment, one must know all the factors that affect the system or are determined by the system. As a rule, the researcher includes in the composition of the system and its environment all those objects that seem to him the most important, describes the internal relations of the system as completely as possible, and pays more attention to its most important properties, neglecting those properties that, in his opinion, opinion do not play significant role. This idealization method is widely used, for example, in physics and chemistry. Biologists, sociologists, economists, and other scientists interested in living systems and their behavior are in a more difficult position. In these sciences it is very difficult to distinguish the essential variables of systems from the non-essential ones; in other words, the problem of specification of the studied set of objects and its subsequent division into two sets - the system and the environment - is here a fundamental difficulty.
From the definition of system and environment, it follows that any system can be divided into subsystems. Objects belonging to one subsystem can be considered as parts of the environment of another subsystem. The analysis of a subsystem requires, of course, the consideration of a new set of relations. Of course, the behavior of a subsystem cannot be completely analogous to the behavior of the system that includes it. In particular, such a property of systems as the hierarchical ordering of the system, in fact, reflects the possibility of dividing the system into subsystems. In other words, it can be said that parts of a system can themselves be systems of lower orders. One method of studying a complex system is to examine in detail the behavior of one of its subsystems. Another method is to observe only the macroscopic behavior of the system as a whole. Both of these methods are widely used in various fields of knowledge, and both of them are important.
In the definition of the system, it is noted that all systems are characterized by the presence of relationships between objects and between their attributes.
If every part of the system is so related to every other part that a change in some part causes a change in all other parts.
tyakh and in the whole system as a whole, then the system behaves as an integrity, or as some connected formation.
If in a set of completely unrelated objects, a change in each part of the set depends only on this part itself, and the change in the set as a whole is the physical sum of changes in its separate parts, then such a collection is called isolated or physically additive.
Integrity and isolation, obviously, are not two different properties, but the limiting values of some measure of the same property. Integrity and separateness differ in the degree to which this property is present, and there is currently no method to measure them. The term "complex" is often used to describe a set of parts that are independent of each other, and the term "system" is used only when a certain degree of integrity is characteristic of a set of objects. However, it is more correct to use the term "degenerate system" for a set of completely independent parts.
Modeling is the replacement of one system (original) with another (model) and the study of the properties of the original by examining the properties of the model. Substitution is made in order to simplify the study of the properties of the original.
In general, the original system can be any natural or artificial, real or abstract system. It has a certain set of parameters and is characterized by certain properties. The system manifests its properties under the influence of external influences. The set of system parameters and their values reflects its internal content - composition, structure and functioning algorithms. The set and values of parameters distinguish the system from other systems. The characteristics of a system are basically its external signs, which are important when interacting with other systems. The characteristics of the system are functionally dependent on its parameters. Obviously, each characteristic of the system is determined mainly by a limited subset of parameters. It is assumed that the influence of other system parameters on the value of this characteristic of the system can be neglected. As a rule, researchers are only interested in certain characteristics of the system under study under specific external influences on the system.
A model is also a system with its own sets of parameters and characteristics, correspondingly reflecting the sets of parameters and characteristics of the original system. With some approximation, we can assume that the characteristics of the model are related to the characteristics of the original.
In this case, the set of characteristics of the model is a reflection of the set of interesting characteristics of the original. Modeling is advisable when the model does not have those features of the original that prevent its study, or there are parameters different from the original that contribute to the study of the properties of the model.
Modeling theory is an interconnected set of provisions, definitions, methods and tools for creating and studying models. These provisions, definitions, methods and tools, as well as the models themselves, are the subject of modeling theory. The main task of modeling theory is to equip researchers with a methodology for creating such models that accurately and completely capture the properties of interest of the originals, are easier or faster to study and ensure the use of its results to obtain the necessary data on the characteristics of the simulated system originals. Modeling theory is the main component of the general theory of systems - systemology, in which the feasibility of models is postulated as the main principle: the system is represented by a finite set of models, each of which reflects a certain facet of its essence.
1.2. System classification
When considering systems, you can use various ways to classify them: by origin, according to the description of input and output
variables, according to the description of the system operator, according to the type of control.
On fig. 1.1 shows a diagram of a two-level classification of systems by origin. If the completeness of the classification of the first level is logically clear, then the second level is clearly incomplete. The classification of natural systems is clear from the figure, its incompleteness is obvious. The incompleteness of the division of artificial systems is associated, for example, with the still incomplete development of systems artificial intelligence. Examples of subclasses of mixed systems include ergonomic systems (machine-human-operator complexes), biotechnical systems (systems that include living organisms and technical devices), and organizational systems (consisting of teams of people who are equipped with the necessary technical means).
S Y S T E M S |
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NATURAL |
ARTIFICIAL |
MIXED |
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Mechanisms |
Ergonomic |
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Biotechnical |
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Environmental |
Automata |
Organizational |
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Social |
. . . . . . . . . . . . . . . |
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. . . . . . . . . . . . |
. . . . . . . . . . . . |
Rice. 1.1. Classification of systems by origin.
The three-level classification scheme of systems according to the type of input, output and internal variables is shown in fig. 1.2. There is a fundamental difference between variables described qualitatively and quantitatively, which is the basis of the first level of classification. For completeness, a third class has been introduced; it includes systems in which some of the variables are of a qualitative nature, and the rest are quantitative. At the next level of classification of systems with qualitative variables, there are cases where the description is carried out by means of a natural language, and cases that allow deeper formalization. The second level of classification of systems with quantitative variables is caused by differences in the methods of discrete and continuous mathematics, which is reflected in the names of the introduced subclasses; the case is also envisaged when the system has both continuous and discrete variables. For systems with a mixed quantitative-qualitative description of variables, the second level is the union of subclasses of the first two classes and is not shown in the figure. The third level of classification is the same for all subclasses of the second level and is depicted for only one of them.
S Y S T E M S |
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WITH QUALITY |
WITH QUANTITATIVE |
WITH MIXED |
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VARIABLES |
VARIABLES |
DESCRIPTION |
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VARIABLES |
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description |
Discrete |
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formalized |
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description |
continuous |
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mixed |
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description |
mixed |
deterministic |
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Stochastic |
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mixed |
Rice. 1.2. A fragment of the classification of systems according to the description of variables.
The next classification (Fig. 1.3) is by the type of the system operator, i.e., the classification of the types of relationships between input and output variables.
S Y S T E M S |
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NONPARAMETER- |
PARAMETERS- |
WHITE BOX |
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DRAWED |
CALLED |
(operator |
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(operator |
known |
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unknown) |
(operator |
(operator |
fully) |
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known |
known |
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partially) |
to parameters) |
Inertial (with memory)
Inertialess (no memory)
Closed (with feedback)
Open (without feedback)
Linear
Nonlinear
Quasilinear
Rice. 1.3. A fragment of the classification of systems according to the type of operators.
At the first level, there are classes of systems that differ in the degree of availability of information about the system operator. The branch of the "black box" ends at this level: the operator is generally considered unknown. The more information about the operator is available, the more differences can be considered and the more developed the classification will be. For example, information about an operator may be so generic that a description of the system cannot be obtained in a parameterized functional form. A non-parameterized class of systems and fits similar situations with very limited information about the operator.
Our knowledge about the operator can have a level that allows us to make a parametric description of this operator, i.e., write down the dependence of the system output y (t) on the system input x (t) in explicit form up to a finite number of parameters θ = (θ 1 , K , θ k ) : y (t ) = Φ (x (), θ ) , where Φ denotes the system operator. Such systems belong to the third class in the classification of this species.
Finally, if the operator parameters are specified exactly, then any uncertainty disappears and we have a system with a fully defined operator, i.e., a “white box”.
Further levels of classification in fig. 1.3 are given only for systems of the third and fourth classes (“black box” is not subject to
further classification, and the classification of non-parametrized systems is related to the type of information available about their operators). The second, third and fourth levels are clear from the drawing itself. Of course, the classification can be continued (for example, linear operators are usually divided into differential, integral, etc.).
Considering the output y (t) of the system (this can be a vector) as its response to controlled u (t) and uncontrolled w (t) inputs - x (t) = (u (t), w (t)), the “black box" can be represented as a set of two processes: X = (x (t ), t T ) and Y = ( y (t ), t T ) . If we consider y (t ) the result of some transformation Φ of the process x (t ) , i.e. y (t ) = Φ (x (t )) , then the "black box" model assumes that this transformation is unknown. In the same case, when we are dealing with a "white box", the correspondence between input and output can be described in one way or another. Which way depends on what we know and in what form this knowledge can be used.
The scheme of the next method of classifying systems - by type of control - is shown in fig. 1.4. The first level of classification is determined by whether the control unit is included in the system or is external to it; a class of systems is also distinguished, the control of which is divided and partially carried out from the outside, and partially - within the system itself. Regardless of whether the control block is included in the system or removed from it, four main types of control can be distinguished, which is reflected at the second level of classification. These types differ depending on the degree of availability of information about the trajectory of the system in the state space, leading the system to the goal, and the ability of the control unit to ensure the evolution of the system along this trajectory.
S Y S T E M S |
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WITH EXTERNAL |
SELF-GOVERNED |
WITH COMBINED |
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MANAGEMENT |
MANAGEMENT |
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no feedback |
Program control |
Automatic |
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Regulation |
Automatic control |
semi-automatic |
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Control |
Parametric adaptation |
automated |
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by parameters |
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Control |
Structural adaptation |
Organizational |
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by structure |
(self-organization) |
Rice. 1.4. Classification of systems by type of control.
System analysis involves: the development of a systematic method for solving a problem, i.e. a logically and procedurally organized sequence of operations aimed at choosing the preferred solution alternative. System analysis is implemented practically in several stages, however, there is still no unity regarding their number and content, because. There is a wide variety of applied problems in science.
Here is a table that illustrates the main patterns of system analysis of three different scientific schools . (Slide 17)
In the process of system analysis, various methods are used at its different levels. System analysis plays the role of a methodological framework that combines all the necessary methods, research techniques, activities and resources for solving problems. In essence, systems analysis organizes our knowledge of an object in such a way as to help select the right strategy or predict the results of one or more strategies that seem appropriate to those who have to make decisions. In the most favorable cases, the strategy found through systems analysis is "best" in some specific sense.
Consider the methodology of system analysis on the example of the theory of the English scientist J. Jeffers. To solve practical problems, he proposes to distinguish seven stages, which are reflected in Slide 18.
Stage 1 "Problem selection". Realizing that there is some problem that can be investigated with the help of systems analysis, important enough to study in detail, is not always a trivial step. The very understanding that a truly systematic analysis of the problem is needed is as important as choosing the right research method. On the one hand, one can tackle a problem that is not amenable to system analysis, and on the other hand, one can choose a problem that does not require the full power of system analysis for its solution, and it would be uneconomical to study by this method. This duality of the first stage makes it critical to the success or failure of the entire study. In general, the approach to solving real problems really requires a lot of intuition, practical experience, imagination and what is called "flair". These qualities are especially important when the problem itself, as often happens, is rather poorly studied.
Stage 2 "Statement of the problem and limitation of its complexity." Once the existence of the problem is recognized, it is required to simplify the problem so that it is likely to have an analytical solution, while retaining all those elements that make the problem interesting enough for practical study. Here again we are dealing with a critical stage in any systems research. The conclusion about whether to consider this or that aspect of a given problem, as well as the results of comparing the significance of a particular aspect for an analytical reflection of the situation with its role in complicating the problem, which may well make it unsolvable, often depends on the accumulated experience in applying systems analysis. It is at this stage that you can make the most significant contribution to solving the problem. The success or failure of the whole study depends largely on a delicate balance between simplification and complexity - a balance that retains all the links to the original problem that are sufficient for the analytical solution to be interpretable. Not a single tempting project turned out to be, in the end, unrealized due to the fact that the accepted level of complexity made subsequent modeling difficult, not allowing to obtain a solution. And, on the contrary, as a result of many systematic studies carried out in various fields of ecology, trivial solutions of problems were obtained, which in fact constituted only subsets of the original problems.
Stage 3 "Establishing a hierarchy of goals and objectives." After setting the task and limiting the degree of its complexity, you can begin to set the goals and objectives of the study. Usually these goals and objectives form a certain hierarchy, with the main tasks being successively subdivided into a number of secondary ones. In such a hierarchy, it is necessary to determine the priorities of the various stages and correlate them with the efforts that need to be made to achieve the goals set. Thus, in a complex study, it is possible to assign relatively low priority to those goals and objectives that, although important from the point of view of obtaining scientific information, have a rather weak influence on the type of decisions made regarding the impact on the system and its management. In another situation, when this task is part of the program of some fundamental research, the researcher is deliberately limited to certain forms of management and concentrates maximum efforts on tasks that are directly related to the processes themselves. In any case, for the fruitful application of systems analysis, it is very important that the priorities assigned to the various tasks are clearly defined.
Stage 4 "Choosing ways to solve problems." On the this stage the researcher can usually choose several ways to solve the problem. As a rule, families of possible solutions to specific problems are immediately visible to an experienced systems analyst. In the general case, he will look for the most general analytical solution, since this will allow him to make maximum use of the results of studying similar problems and the corresponding mathematical apparatus. Each specific problem can usually be solved in more than one way. Again, the choice of the family within which to search for an analytical solution depends on the experience of the systems analyst. An inexperienced researcher can spend a lot of time and money trying to apply a solution from any family, not realizing that this solution was obtained under assumptions that are unfair for the particular case with which he is dealing. The analyst, on the other hand, often develops several alternative solutions and only later settles on the one that best suits his task.
Stage 5 "Modeling". Once suitable alternatives have been analyzed, the next important step is to model the complex dynamic relationships between different aspects of the problem. At the same time, it should be remembered that the processes being modeled, as well as the feedback mechanisms, are characterized by internal uncertainty, and this can significantly complicate both the understanding of the system and its controllability. In addition, the modeling process itself must take into account a complex set of rules that will need to be observed when deciding on an appropriate strategy. At this stage, it is very easy for a mathematician to get carried away by the elegance of the model, and as a result, all points of contact between the real decision-making processes and the mathematical apparatus will be lost. In addition, when developing a model, unverified hypotheses are often included in it, and it is rather difficult to predetermine the optimal number of subsystems. It can be assumed that a more complex model takes into account the complexities of a real system more fully, but although this assumption seems intuitively correct, additional factors must be taken into account. Consider, for example, the hypothesis that a more complex model also gives higher accuracy in terms of the uncertainty inherent in model predictions. Generally speaking, the systematic bias that occurs when a system is decomposed into several subsystems is inversely related to the complexity of the model, but there is also a corresponding increase in uncertainty due to errors in measuring individual model parameters. Those new parameters that are introduced into the model must be quantified in field and laboratory experiments, and there are always some errors in their estimates. After going through the simulation, these measurement errors contribute to the uncertainty of the resulting predictions. For all these reasons, in any model it is advantageous to reduce the number of subsystems included in the consideration.
Stage 6 "Assessment of possible strategies". Once the simulation has been brought to the stage where the model can be used, the stage of evaluating the potential strategies derived from the model begins. If it turns out that the underlying assumptions are incorrect, you may have to return to the modeling stage, but it is often possible to improve the model by slightly modifying the original version. It is usually also necessary to investigate the “sensitivity” of the model to those aspects of the problem that were excluded from the formal analysis at the second stage, i.e. when the task was set and the degree of its complexity was limited.
Stage 7 "Implementation of results". The final stage of the system analysis is the practical application of the results obtained in the previous stages. If the study was carried out according to the above scheme, then the steps that need to be taken for this will be quite obvious. However, systems analysis cannot be considered complete until the research reaches the stage of practical application, and it is in this respect that much of the work done has been left unfulfilled. At the same time, just at the last stage, the incompleteness of certain stages or the need to revise them may be revealed, as a result of which it will be necessary to go through some of the already completed stages again.
Thus, the purpose of multi-stage systems analysis is to help choose the right strategy for solving practical problems. The structure of this analysis is intended to focus the main effort on complex and usually large-scale problems that cannot be solved by simpler methods of research, such as observation and direct experimentation.
SUMMARY
1. The main contribution of system analysis to the solution of various problems is due to the fact that it makes it possible to identify those factors and interrelations that may later turn out to be very significant, that it makes it possible to change the method of observation and experiment in such a way as to include these factors in consideration, and illuminates weak spots hypotheses and assumptions.
2. As a scientific method, systems analysis, with its emphasis on testing hypotheses through experiments and rigorous sampling procedures, creates powerful tools for understanding the physical world and integrates these tools into a system of flexible but rigorous study of complex phenomena.
3. Systematic consideration of the object involves: the definition and study of systemic quality; identification of the totality of elements forming the system; establishing links between these elements; study of the properties of the environment surrounding the system, important for the functioning of the system, at the macro and micro levels; revealing the relationships connecting the system with the environment.
4. The system analysis algorithm is based on the construction of a generalized model that reflects all the factors and relationships of the problem situation that may appear in the solution process. The system analysis procedure consists in checking the consequences of each of the possible alternative solutions for choosing the optimal one according to any criterion or their combination.
In preparing the lecture, the following literature was used:
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The principle of system. System. Basic concepts and definitions
The main starting point of system analysis as a scientific discipline is principle of consistency, which can be perceived as a philosophical principle that performs both ideological and methodological functions. Worldview function the principle of consistency is manifested in the representation of an object of any nature as a set of elements that are in a certain interaction with each other with the outside world, as well as in understanding the systemic nature of knowledge. Methodological function the principle of consistency is manifested in the totality of cognitive means, methods and techniques that are common methodology system research.
The first systematic ideas about nature, its objects and knowledge about them took place in the ancient philosophy of Plato and Aristotle. Throughout the history of the formation of system analysis, ideas about systems and the patterns of their construction, functioning and development have been repeatedly refined and rethought. The term “system” is used in those cases when they want to characterize the object under study or the designed object as something whole (single), complex, about which it is impossible to immediately give an idea, showing it, graphically describing it with a mathematical expression.
Comparing the evolution of the definition of the system (connection elements, then the goal, then the observer) and the evolution of the use of the categories of the theory of knowledge in research activities, one can find similarities: at the beginning, models (especially formal ones) were based on taking into account only elements and connections, interactions between them, then - attention began to be paid goals, the search for methods of its formalization representation (objective function, functioning criterion, etc.), and, starting from the 60s. increasing attention is being paid to observer, the person performing the simulation or conducting the experiment, i.e. decision maker. The Great Soviet Encyclopedia gives the following definition: “a system is an objective unity of objects, phenomena, and knowledge about nature and society that are naturally connected with each other”), i.e. it is emphasized that the concept of an element (and, consequently, of a system) can be applied both to existing, materially realized objects, and to knowledge about these objects or about their future implementations. Thus, in the concept of a system, the objective and the subjective constitute a dialectical unity, and we should talk about the approach to the objects of study as systems, about their different representation at different stages of cognition or creation. In other words, different concepts can be put into the term “system” at different stages of its consideration, as if speaking about the existence of a system in various forms. M. Mesarovic, for example, suggests highlighting strata consideration of the system. Similar strata can exist not only during the creation, but also during the cognition of the object, i.e. when displaying real-life objects in the form of systems abstractly represented in our minds (in models), which will then help create new objects or develop recommendations for transforming existing ones. The system analysis technique can be developed not necessarily covering the entire process of cognition or system design, but for one of its strata (which, as a rule, happens in practice), and in order to avoid terminological and other disagreements between researchers or system developers , it is necessary, first of all, to clearly stipulate what kind of stratum of consideration we are talking about.
Considering the various definitions of the system and their evolution, and not highlighting any of them as the main one, it is emphasized that at different stages of representing an object as a system, in specific situations, different definitions can be used. Moreover, as the ideas about the system are refined or when moving to another stratum of its study, the definition of the system not only can, but must be refined. A more complete definition, including both elements, and connections, and goals, and an observer, and sometimes his "language" of displaying the system, helps to set the task, to outline the main stages of the system analysis methodology. For example, in organizational systems, if you do not determine the person competent to make decisions, you may not achieve the goal for which the system is created. Thus, when conducting a system analysis, you must first of all display the situation using the most complete definition of the system, and then, highlighting the most significant components that affect decision making, formulate a “working” definition that can be refined, expanded, converged depending on the course of the analysis. . At the same time, it should be taken into account that the refinement or concretization of the definition of the system in the process of research entails a corresponding adjustment of its interaction with the environment and the definition of the environment. Hence, it is important to predict not only the state of the system, but also the state of the environment, taking into account its natural artificial inhomogeneities.
The observer selects the system from the environment, which determines the elements included in the system from the rest, i.e. from the environment, in accordance with the objectives of the study (design) or a preliminary idea of the problem situation. In this case, three options for the position of the observer are possible, which:
can attribute itself to the environment and, presenting the system as completely isolated from the environment, build closed models (in this case, the environment will not play a role in the study of the model, although it can influence its formulation);
include yourself in the system and model it taking into account your influence and the influence of the system on your ideas about it (a situation typical of economic systems);
separate oneself from both the system and the environment, and consider the system as open, constantly interacting with the environment, taking this fact into account when modeling (such models are necessary for developing systems).
Consider the basic concepts that help clarify the idea of the system. Under element It is customary to understand the simplest, indivisible part of the system. However, the answer to the question of what is such a part can be ambiguous. For example, as elements of the table, one can name “legs, boxes, a lid, etc.”, or “atoms, molecules”, depending on what task the researcher faces. Therefore, we will accept the following definition: an element is the limit of the division of the system from the point of view of the aspect of consideration, the solution of a specific problem, the goal set. If necessary, you can change the principle of dismemberment, highlight other elements and use the new dismemberment to get a more adequate idea of the analyzed object or problem situation. With a multilevel dismemberment of a complex system, it is customary to single out subsystems and Components.
The concept of a subsystem implies that a relatively independent part of the system is singled out, which has the properties of the system, and in particular, has a subgoal that the subsystem is oriented towards, as well as its own specific properties.
If parts of the system do not have such properties, but are simply collections of homogeneous elements, then such parts are usually called components.
concept connection is included in any definition of the system and ensures the emergence and preservation of its integral properties. This concept simultaneously characterizes both the structure (statics) and the functioning (dynamics) of the system. Communication defines as a limitation of the degree of freedom of elements. Indeed, the elements, entering into interaction (connection) with each other, lose some of their properties, which they potentially possessed in a free state.
concept condition usually characterize a "cut" of the system, a stop in its development. If we consider the elements (components, functional blocks), take into account that the “outputs” (output results) depend on , y and x, i.e. g=f(,y,x), then, depending on the task, the state can be defined as (,y),(,y,g) or (,y,x,g).
If the system is capable of transitioning from one state to another (for example,
), then it is said to have command. This concept is used when unknown patterns (rules) of transition from one state to another. Then they say that the system has some kind of behavior and find out its nature, the algorithm. Given the introduction of notation, behavior can be represented as a function
concept equilibrium is defined as the ability of a system in the absence of external disturbing influences (or under constant influences) to maintain its state for an arbitrarily long time. This state is called a state of balance. For economic organizational systems, this concept is applicable rather conditionally.
Under conventionality understand the ability of a system to return to a state of equilibrium after it has been brought out of this state under the influence of external (or in systems with active elements - internal) disturbing influences. This ability is inherent in systems at constant Y only when the deviations do not exceed a certain limit. A state of balance. To which the system is able to return is called stable state of equilibrium.
Regardless of the choice of system definition (which reflects the accepted concept and is actually the beginning of modeling), it has the following signs:
integrity - a certain independence of the system from the external environment and from other systems;
connectedness, i.e. the presence of connections that allow, through transitions along them from element to element, to connect any two elements of the system, - The simplest connections are serial and parallel connections of elements, positive and negative feedback;
functions - the presence of goals (functions, capabilities) that are not a simple sum of sub-goals (sub-functions, capabilities) of the elements included in the system; the irreducibility (degree of irreducibility) of the properties of a system to the sum of the properties of its elements is called emergence.
The orderliness of relations connecting the elements of the system determine the structure of the system as a set of elements that function in accordance with the connections established between the elements of the system. Links determine the order of exchange between the elements of matter, energy, information, which is important for the system.
The functions of the system are its properties that lead to the achievement of the goal. The functioning of the system is manifested in its transition from one state to another or in the preservation of any state for a certain period of time. That is, the behavior of the system is its functioning in time. Purposeful behavior is focused on achieving the system's preferred goal.
Large systems are systems that include a significant number of elements with the same type of connections. Complex systems are systems with a large number of elements of various types and with heterogeneous relationships between them. These definitions are very arbitrary. More constructive is the definition of a large complex system as a system, at the upper levels of control of which all information about the state of the elements of the lower level is not needed and even harmful.
Systems are open and closed. Closed systems have well-defined, rigid boundaries. For their functioning, protection from environmental influences is necessary. Open systems exchange energy, information and matter with the environment. Exchange with the external environment, the ability to adapt to external conditions is an indispensable condition for open systems to exist. All organizations are open systems.
The concept of "system structure" plays a key role in the analysis and synthesis of systems, and the following thesis (law) of cybernetics is essential.
"There are laws of nature that govern the behavior of large multi-connected systems of any nature: biological, technical, social and economic. These laws relate to the processes of self-regulation and self-organization and express precisely those "guiding principles" that determine growth and stability, learning and regulation, adaptation and the evolution of systems. various systems from the point of view of cybernetics they are exactly the same, since they demonstrate the so-called viable behavior, the purpose of which is survival.
Such behavior of the system is determined not so much by the specific processes occurring in it itself, or by the values that even the most important of its parameters take, but, first of all, by its dynamic structure, as a way of organizing the interconnection of individual parts of a single whole. The most important elements of the system structure are the contours feedback and mechanisms of conditional probabilities, which provide self-regulation, self-learning and self-organization of the system. The main result of the system's activity is its outcomes. In order for the outcomes to meet our goals, it is necessary to organize the structure of the system in an appropriate way. "That is, to obtain the required outcomes, it is necessary to be able to influence feedbacks and mechanisms of conditional probabilities, as well as be able to evaluate the results of these influences.
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