Due to the fact that system analysis is aimed at solving any problems, the concept of a system should be very general, applicable to any situation. The way out is seen in designating, listing, describing such features, properties, features of systems that, firstly, are inherent in all systems without exception, regardless of their artificial or natural origin, material or ideal embodiment; and secondly, from a variety of properties, they would be selected and included in the list on the basis of their necessity for the construction and use of systems analysis technology. The resulting list of properties can be called a descriptive (descriptive) definition of the system.
The properties of the system we need naturally fall into three groups, four properties each.
System static properties
Static properties are the features of a particular state of the system. This is, as it were, something that can be seen on an instantaneous photograph of the system, something that the system has at any, but a fixed point in time.Dynamic properties of the system
If we consider the state of the system at another, different from the first, moment in time, then we will again find all four static properties. But if you superimpose these two "photographs" on top of each other, you will find that they differ in details: during the time between the two moments of observation, some changes occurred in the system and its environment. Such changes may be important when working with the system and, therefore, should be reflected in the descriptions of the system and taken into account in working with it. Features of changes over time inside the system and outside it are called the dynamic properties of systems. If static properties are what can be seen in a photograph of a system, then dynamic properties are what will be found when watching a movie about the system. We can talk about any changes in terms of changes in the static models of the system. In this regard, four dynamic properties are distinguished.Synthetic properties of the system
This term denotes generalizing, collective, integral properties, taking into account what has been said before, but emphasizing the interaction of the system with the environment, on integrity in the most general sense.From an infinite number of properties of systems, twelve inherent in all systems are singled out. They are selected on the basis of their necessity and sufficiency for substantiation, construction and accessible presentation of the technology of applied systems analysis.
But it is very important to remember that each system is different from all others. This is manifested, first of all, in the fact that each of the twelve system-wide properties in a given system is embodied in an individual form specific to this system. In addition, in addition to these general system regularities, each system has other properties that are unique to it.
Applied systems analysis is aimed at solving a specific problem. This is expressed in the fact that, with the help of a system-wide methodology, it is technologically aimed at discovering and using individual, often unique features of a given problem situation.
To facilitate such work, some classifications of systems can be used, fixing the fact that different models, different techniques, different theories should be used for different systems. For example, R. Ackoff and D. Garayedaghi proposed to distinguish systems according to the ratio of objective and subjective goals in parts of the whole: technical, man-machine, social, ecological systems. Another useful classification, according to the degree of knowledge of systems and the formalization of models, was proposed by W. Checkland: "hard" and "soft" systems and, accordingly, "hard" and "soft" methodologies, discussed in Ch. one.
So, we can say that the systemic vision of the world consists in understanding its general systemic nature and proceeding to consider a specific system, focusing on its individual features. The classics of systems analysis formulated this principle aphoristically: "Think globally, act locally."
Tarasenko F. P. Applied system analysis (science and art of problem solving): Textbook. - Tomsk; Tomsk University Press, 2004. ISBN 5-7511-1838-3. Fragment
BASICS OF INFORMATION TECHNOLOGIES
Topic 6. MATHEMATICAL MODELING AND NUMERICAL METHODS
Basic concepts and definitions. Fundamentals of system analysis
Natural science can be represented as consisting of three parts: empirical, theoretical and mathematical.
Empirical part contains factual information obtained in experiments and observations, as well as from their primary systematization.
Theoretical part develops theoretical concepts that make it possible to unite and explain from a unified position a significant complex of phenomena, and formulates the main patterns that empirical material obeys.
Mathematical part constructs mathematical models that serve to test the basic theoretical concepts, provides methods for the primary processing of experimental data so that they can be compared with the results of the models, and develops methods for planning an experiment in such a way that, with a small expenditure of effort, it is possible, if possible, from experiments obtain sufficiently reliable data.
Such a scheme corresponds to the structure of many natural sciences, but the development of various parts, especially mathematical models at the present time in the socio-economic field, is completely incomparable, say, with physics, mechanics and astronomy.
This circumstance is due, on the one hand, to the fact that the development of theoretical concepts and mathematical models in ecology began much later than in the named sciences, and, on the other hand, to the fact that the nature of the biological phenomena being studied is much more complicated, which makes it necessary to take into account much more factors in building models of ecological processes than physical ones. In everyday life, this last circumstance is usually referred to as the specific complexity of life processes.
In addition, the construction of mathematical models in ecology is greatly hindered by the fact that most ecologists, chemists, biologists and other specialists do not have sufficient knowledge of mathematics, and few mathematicians have relevant interests and sufficient knowledge in the above areas.
The contradictions between the unlimited desires of a person to know the world and the limited existing opportunities to do this, between the infinity of nature and the finiteness of human resources have many important consequences, including in the very process of human cognition of the surrounding world. One of such features of cognition, which allow gradually, step by step, to resolve these contradictions, is the presence of analytical and synthetic ways of thinking.
The essence of analysis is to divide the whole into parts, to represent the complex as a set of simpler components. But in order to cognize the whole, the complex, the reverse process is also necessary - synthesis. This applies not only to individual thinking, but also to universal human knowledge.
The analyticity of human knowledge is reflected in the existence of various sciences, in the continuing differentiation of sciences, in an ever deeper study of ever narrower questions, each of which is nevertheless interesting, important and necessary in itself. At the same time, the reverse process of knowledge synthesis is also necessary. This is how "frontier" sciences such as biochemistry, physical chemistry, geochemistry, geophysics, biophysics or bionics, etc., arise. However, this is only one form of synthesis. Another, higher form of synthetic knowledge is realized in the form of sciences about the most general properties of nature. Philosophy reveals and displays all common properties of all forms of matter; mathematics studies some, but also general, relations. The synthetic sciences also include systems sciences: cybernetics, systems theory, organization theory, etc. They necessarily combine technical, natural and humanitarian knowledge.
So, the dismemberment of thinking (into analysis and synthesis) and the interconnectedness of these parts are obvious signs of a systematic cognition.
In the analysis and synthesis of large systems, such as natural ecological complexes, a systematic approach has been developed, which differs from the classical (or inductive) approach. The latter examines the system by moving from the particular to the general and synthesizes (constructs) the system by merging its components, developed separately. In contrast, the systematic approach involves a consistent transition from the general to the particular, when the consideration is based on the goal, and the object under study is distinguished from the environment. So what is a systems approach?
Definition: Systems approach is a modern methodology for studying and solving problems that are, as a rule, interdisciplinary in nature. A systematic approach means only the desire to study one or another phenomenon or object, taking into account the maximum number of internal connections and external factors that determine the functioning of the object, i.e. the desire to study it in all dialectical complexity, revealing all internal contradictions. It is necessary to distinguish between the concepts of a systems approach and systems analysis.
Definition: System analysis is a set of methods, techniques, procedures based on the use of modern information processing capabilities and the "man-machine" dialogue. Any systematic study ends with an assessment of the quality of the system's functioning, a comparison of different project options.
Contrary to the ideas of many ecologists, system analysis is not some kind of mathematical method, and not even a group of mathematical methods. This is a broad strategy of scientific research, which, of course, uses the mathematical apparatus and mathematical concepts, but within the framework of a systematic scientific approach to solving complex 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 particular sense.
We will understand by system analysis the ordered and logical organization of data and information in the form of models, accompanied by rigorous testing and research of the models themselves, necessary for their verification and subsequent improvement. In turn, we can consider models as formal descriptions of the main elements of a natural science problem in physical or mathematical terms. Previously, the main emphasis in explaining certain phenomena was made on the use of physical analogies of biological and ecological processes. Systems analysis also sometimes refers to physical analogies of this kind, but the models used here are more often mathematical, and fundamentally abstract.
As we noted above, there is a difference in the essence of the concepts of "system approach" and "system analysis". Academician N.N. Moiseev noted the following about this: “If system analysis provides the means for research, forms the tools of modern interdisciplinary scientific activity, then the system approach determines, if you like, its “ideology”, direction, forms its concept. Means and objectives of the study - this is how, in a somewhat aphoristic form, the difference between these terms can be explained.
The concept of a system. Let us define the basic concepts of system analysis. So, element let's name some object (material, energetic, informational) that has a number of important properties for us, but the internal structure (content) of which is irrelevant to the purpose of consideration. Another important concept - connection - important for the purposes of consideration of the exchange between the elements of matter, energy, information.
System is defined as a set of elements with the following features:
a) connections that allow, by means of transitions along them from element to element, to connect any two elements of the collection (connectivity of the system);
b) a property (purpose, function) that is different from the properties of individual elements of the population (function of the system).
System analysis as a general scientific approach, is focused on conducting interdisciplinary (complex) research in various fields of human knowledge.
There are many definitions of the concept system ”, among the most significant features of the system, we note the following:
1) the system consists of separate parts (elements), between which certain relationships (connections) are established;
2) sets of elements form subsystems;
3) the system has a certain structure, which is understood as a set of elements of the system and the nature of the relationship between them;
4) each system can be considered as a part of a higher order system (principle of hierarchy);
5) the system has certain boundaries that characterize its isolation from the environment;
6) according to the degree of “transparency” of the boundaries of the system, they are divided into open and closed;
7) links are classified into intra-system and inter-system, positive and negative, direct and reverse;
8) the system is characterized by stability, the degree of self-organization and self-regulation.
Modeling is central to systems analysis. Model - this is an object (material, ideal), which reproduces the most essential features and properties of the phenomenon or process under consideration. The purpose of building a model is to obtain and / or expand knowledge about the object under study.
A large system is a system that includes a significant number of elements of the same type and links of the same type. A complex system is a system consisting of elements of different types and having heterogeneous connections between them. System structure called its division into groups of elements indicating the links between them, unchanged for the entire time of consideration and giving an idea of the system as a whole.
Decomposition called the division of the system into parts, convenient for any operations with this system. Hierarchy let's call the structure with the presence of subordination, i.e. unequal links between elements, when impacts in one of the directions have a much greater impact on the element than in the other.
After defining these fundamental concepts, we can proceed to the classification of types of system modeling.
Methods of system analysis. When solving specific problems of system analysis, the general method is differentiated into various particular methods, which, depending on the degree of use of formal elements in them, can be divided into three groups:
1) mathematical (formal);
2) heuristic (informal);
3) combined mathematical and heuristic methods.
These methods are used in system analysis:
1) to determine the numerical values of indicators characterizing the results of the system functioning;
2) to search for the best options for actions leading to the achievement of certain results (optimization);
3) for processing and analyzing heuristic data (for example, data from expert environmental assessments).
When solving problems of the first group, almost all known mathematical methods are used (differentiation, integral and vector calculus, set theory, probability theory, mathematical statistics, network modeling, response function analysis, stochastic modeling, stability research, graph theory, mathematical modeling, control theory etc.).
When solving optimization problems for the study of optimal strategies for managing the natural environment, the methods of operations research (linear, dynamic and other types of programming, queuing theory, game theory) are most widely used. This work should be preceded by a full-scale verification of dynamic models and control actions used in optimization studies.
The main mathematical apparatus for processing heuristic data is probability theory and mathematical statistics.
Despite the increasing role of mathematical methods, it cannot be assumed that the formal methods of modern mathematics will turn out to be a universal means of solving all the problems that arise in the field of ecology. Methods that use the results of experience and intuition, i.e. heuristic (informal) ones will undoubtedly retain their significance in the future.
The procedures for the formation of the goals of the system, options for their implementation, models, criteria cannot be fully formalized.
In this regard, a feature of heuristic methods is that the expert, when evaluating events, mainly relies on the information contained in his experience and intuition.
Combined mathematical and heuristic methods. Among the combined mathematical methods, the following can be distinguished:
situation method.
Delphi method.
Structurization method.
Decision tree method.
Simulation modeling, including business games.
Among the heuristic and combined methods of system analysis, the most famous are:
Heuristic: writing scripts; morphological method; method of collective generation of ideas; determining the degree of preference.
Combined: situation method; method "Delphi"; structuring method; decision tree method; simulation modeling, including business games.
The scope of possible applications of these methods:
Determination of the list of goals and ways to achieve them;
Determining the preference (ranking) of individual
goals, ways, activities, results, etc.;
Decomposition of goals, programs, plans, etc. on their
constituent elements;
Choosing the best ways to achieve your goals;
Selection of criteria for comparing goals and ways to achieve them;
Building models for choosing goals and ways to achieve them;
Synthesis of data analysis of the functioning of the system as a whole.
Listed methods of system analysis should not be opposed to each other. Each has its own advantages and disadvantages, but none of them can be considered universal, suitable for solving any problems. The best results can be obtained by a combination of several methods, depending on the nature of the problem being solved. With the transition to higher levels of management, goals and other elements of system analysis become more and more qualitative, the importance of methods based on on expert assessments . The complexity of modeling the processes occurring in natural ecosystems further complicates the application of mathematical methods. At the same time, the role of the uncertainty factor is increasing; avoidance of consideration of uncertainty, especially inherent in mathematical methods of analysis, can lead to incorrect conclusions.
System analysis seeks to determine the relationship between a large number of quantitative parameters, thus it is more or less associated with the use of mathematical tools. Thus, the success of the analysis depends on the degree of familiarity with the series. special techniques of mathematics .
Chapter 11, Fundamentals of Systems Analysis
11.1. The main varieties of system analysis
Types of system analysis
System analysis is an important object of methodological research and one of the most rapidly developing scientific areas. Numerous monographs and articles are devoted to him. Its most famous researchers are: V. G. Afanasiev, L. Bertalanfi, I. V. Blauberg, A. A. Bogdanov, V. M. Glushkov, T. Hobbes, O. Comte, V. A. Kartashov, S. A. Kuzmin, Yu. G. Markov, R. Merton, M. Mesarovich, T. Parsons, L. A. Petrushenko, V. N. Sadovsky, M. I. Setrov, G. Spencer, V. N. Spitsnadel , Ya. Takahara, V. S. Tyukhtin, A. I. Uemov, W. Churchman, E. G., Yudin, etc.
The popularity of systems analysis is now so great that one can paraphrase the well-known aphorism of the eminent physicists William Thomson and Ernest Rutherford regarding a science that can be divided into physics and stamp collecting. Indeed, among all methods of analysis, systems analysis is the real king, and all other methods can be safely attributed to its inexpressive servants.
At the same time, whenever the question of system analysis technologies is raised, insurmountable difficulties immediately arise due to the fact that there are no well-established intelligent systems analysis technologies in practice. There is only some experience with the systems approach in different countries. Thus, there is a problematic situation, characterized by an ever-increasing need for the technological development of system analysis, which has been developed very insufficiently.
The situation is aggravated not only by the fact that intellectual technologies for system analysis have not been developed, but also by the fact that there is no unambiguous understanding of the system analysis itself. This is despite the fact that already 90 years have passed since the publication of the fundamental work in the field of systems theory - "Tectology" by A. A. Bogdanov, and the history of the development of system ideas has almost half a century.
Several options for understanding the essence of system analysis stand out quite prominently:
- 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 by a system approach in 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.
In this case, what is called system analysis is an insufficiently integrated array of methods and techniques of system activity. In table. 31 gives a description of the main types of systemic activities, among which systemic analysis is actually lost.
| Activities | Purpose of activity | Means of activity | Activity content |
|---|---|---|---|
| System cognition | Gaining knowledge | Knowledge, methods of cognition | Study of the object and its subject |
| System analysis | Understanding the Problem | Information, methods of its analysis | Consideration of the problem through methods of analysis |
| System Modeling | Create a system model | Modeling methods | Building a formal or full-scale model of the system |
| Systems engineering | System creation | Construction Methods | System design and objectification |
| System Diagnostics | System Diagnosis | Diagnostic methods | Clarification of deviations from the norm in the structure and functions of the system |
| System assessment | System evaluation | Theory and methods of evaluation | Obtaining an assessment of the system, its significance |
Table 31 - Types of system activities and their characteristics
It should be emphasized that nowadays there are practically no scientific and pedagogical developments in various areas of management in which attention would not be paid to system analysis. At the same time, it is quite rightly considered as an effective method for studying objects and management processes. However, there is practically no analysis of the “points” of applying system analytics to solving specific management problems, and there is a shortage of technological schemes for such an analysis. System analysis in management is currently not a developed practice, but growing mental declarations that do not have any serious technological support.
System Analysis Methodology
The methodology of system analysis is a rather complex and variegated set of principles, approaches, concepts and specific methods. Let's consider its main components.
Principles are understood as the basic, initial provisions, some general rules of cognitive activity that indicate the direction of scientific knowledge, but do not indicate a specific truth. These are developed and historically generalized requirements for the cognitive process that perform the most important regulatory roles in cognition. Substantiation of the principles is the initial stage of building a methodological concept.
The most important principles of system analysis include the principles of elementarism, universal connection, development, integrity, consistency, optimality, hierarchy, formalization, normativity and goal setting. System analysis is represented as an integral of these principles. In table. 32 shows their characteristics in terms of system analysis.
| Principles of system analysis | Characteristic |
|---|---|
| Elementarism | The system is a set of interconnected elementary components |
| Universal connection | The system acts as a manifestation of the universal interaction of objects and phenomena |
| Development | Systems are in development, they go through the stages of emergence, formation, maturity and downward development |
| Integrity | Consideration of any object, system from the point of view of internal unity, separation from the environment |
| Consistency | Consideration of objects as a system, i.e. as integrity, which is not reduced to a set of elements and relationships |
| Optimalities | Any system can be brought to the state of its best functioning in terms of some criterion |
| Hierarchies | The system is a subordinate formation |
| Formalizations | Any system with greater or lesser correctness can be represented by formal models, including formal-logical, mathematical, cybernetic, etc. |
| normativity | Any system can only be understood if it is compared with some normative system. |
| goal setting | Any system tends to a certain state that is preferable for it, which acts as the goal of the system. |
Table 32 - Principles of system analysis and their characteristics
Methodological approaches in system analysis combine a set of techniques and methods of implementing system activities that have developed in the practice of analytical activity. The most important among them are systemic, structural-functional, constructive, complex, situational, innovative, targeted, activity, morphological and program-targeted approaches. Their characteristics are presented in table. 33.
| Approaches in systems analysis | Characteristics of approaches in system analysis |
|---|---|
| Systemic |
|
| Structural-functional |
|
| Constructive |
|
| Complex |
|
| Problem |
|
| situational |
|
| Innovative |
|
| Normative |
|
| Target |
|
| activity |
|
| Morphological |
|
| Program target |
|
Table 33 - Characteristics of the main approaches in system analysis
Methods are the most important, if not the main component of the system analysis methodology. Their arsenal is quite large. The approaches of the authors in their selection are also varied. Yu. I. Chernyak divides the methods of system research into four groups: informal, graphic, quantitative and modeling. A. V. Ignatieva and M. M. Maksimtsov give a classification of methods for studying control systems, dividing them into three main groups: 1) methods based on the use of knowledge and intuition of specialists; 2) methods of formalized representation of systems; and 3) complex methods.
In our opinion, the methods of system analysis have not yet received a sufficiently convincing classification in science. Therefore, VN Spitsnadel is right, who notes that, unfortunately, there is no classification of these methods in the literature, which would be unanimously accepted by all experts. Given table. 34 presents a possible version of such a classification developed by the author. It is proposed to use the type of knowledge processed by the method as the basis for classification; the method of realization, which can be either intuition or knowledge; the functions performed, which are reduced to the receipt, presentation and processing of information; level of knowledge - theoretical or empirical; form of knowledge representation, which can be qualitative or quantitative.
| Basis of classification | Methods of system analysis |
|---|---|
| Type of knowledge |
|
| Way of implementation |
|
| Functions performed |
|
| Level of knowledge |
|
| Form of knowledge representation |
|
Table 34 - Methods of system analysis
The methodological complex of system analysis would be incomplete if it does not include its theoretical ensemble. Theory is not only a reflection of reality, but also a method of its reflection, i.e. it performs a methodological function. On this basis, systemic theories are included in the systemic methodological complex. The most important systems theories that affect the analysis are presented in Table. 35.
| Name | The authors | Characteristic |
|---|---|---|
| General systems theory (several options) | A. A. Bogdanov, L. Bertalanffy, M. Mesarovich, W. Ross Ashby, A. I. Uemov, V. S. Tyukhtin, Yu. A. Urmantsev, et al. |
|
| Structuralism (several options) | K. Levi-Strauss, M. P. Foucault, J. Lacan, R. Barthes, L. Goldman, A. R. Radcliffe-Brown and others. |
|
| Functionalism (several options) | G. Spencer, T. Parsons, B. Malinowski, R. Merton, N. Luhmann, K. Gempel, C. Mills and others. |
|
| Structural functionalism (several variants) | R. Bales, R. McIver, R. Merton, T. Parsons, N. Smelser, E. Shils and others. |
|
| System-cybernetic theories | N. Wiener, W. Ross Ashby, R. Ackoff, St. Beer, V. M. Glushkov and others. |
|
| Mathematical systems theory (several options) | M. Mesarovich, L. V. Kantarovich, V. S. Nemchinov and others. |
|
| Synergetics | I. I. Prigozhin, G. Hagen |
|
From Table. 35 it follows that the systems theory is developing in several directions. Such a direction as the general theory of systems is practically exhausting itself, structuralism, functionalism and structural functionalism have been formed in social science, biology, system-cybernetic and mathematical theories have been developed. The most promising direction now is synergetics, which explains the non-stationary systems that a person encounters more and more often in the context of the transition to the post-industrial dynamics of life.
Types of system analysis
The diversity of system analysis methodology is a breeding ground for the development of varieties of system analysis, which are understood as some established methodological complexes. Note that the question of classifying the varieties of system analysis has not yet been developed in science. There are separate approaches to this problem, which are found in some works. Quite often, the types of system analysis are reduced to methods of system analysis or to the specifics of the system approach in systems of various nature. In fact, the rapid development of system analysis leads to the differentiation of its varieties on many grounds, which are: the purpose of system analysis; direction of the analysis vector; the method of its implementation; time and aspect of the system; the branch of knowledge and the nature of the reflection of the life of the system. Classification on these grounds is given in table. 36.
| Basis of classification | Types of system analysis | Characteristic |
|---|---|---|
| Purpose of system analysis | Research system | Analytical activity is built as a research activity, the results are used in science |
| Applied System | Analytical activity is a specific kind of practical activity, the results are used in practice | |
| Direction of the analysis vector | descriptive or descriptive | System analysis starts from structure and goes to function and purpose |
| Constructive | The analysis of a system starts with its purpose and proceeds through functions to structure. | |
| Analysis method | Qualitative | Analysis of the system in terms of qualitative properties, characteristics |
| Quantitative | Analysis of the system in terms of a formal approach, quantitative representation of characteristics | |
| System time | Retrospective | Analysis of systems of the past and their influence on the past and history |
| Actual (situational) | Analysis of systems in situations of the present and problems of their stabilization | |
| predictive | Analysis of future systems and ways to achieve them | |
| Aspects of the system | Structural | Structure analysis |
| Functional | Analysis of the functions of the system, the effectiveness of its functioning | |
| Structural-functional | Analysis of structure and functions, as well as their interdependence | |
| System scale | macrosystem | Analysis of the place and role of the system in larger systems that include it |
| microsystem | Analysis of systems that include this one and affect the properties of this system | |
| branch of knowledge | General systemic | Based on the general theory of systems, carried out from general systemic positions |
| Special system | Based on special systems theory, takes into account the specifics of the nature of systems | |
| Reflection of the life of the system | vital | It involves an analysis of the life of the system, the main stages of its life path |
| Genetic | Analysis of system genetics, inheritance mechanisms |
Table 36 - Characteristics of the varieties of system analysis
This classification allows diagnosing each specific type of system analysis. To do this, it is necessary to “go through” all the bases of classification, choosing the type of analysis that best reflects the properties of the type of analysis used.
Baltic State Technical University "VOENMEH"
BASICS
SYSTEM ANALYSIS
Tutorial
"Publishing House "Business Press"
St. Petersburg
UDC 303.732.4
BBC 65.05
Reviewers:
doctor of technical sciences, professor, head. Department of St. Petersburg State Institute of Fine Mechanics and Optics (Technical University)
Academician of Acmeological Sciences, President of ARISIM, Doctor of Technical Sciences, Professor of St. Petersburg State Academy of Engineering and Economics
C 72 Fundamentals of system analysis: Proc. allowance. - St. Petersburg: "Izd. house "Business Press", 2000 - 326 p.
The textbook presents the history of development and the logical and methodological foundations of system analysis. The practical bases for the use of system analysis in science, technology, economics, and education are considered.
UDC 303.732.4
© Publishing House
"Business Press", 2000
INTRODUCTION
Chapter 1. THE NEED FOR A SYSTEM ANALYSIS, ITS ESSENCE AND TERMINOLOGY
1.1. History of the development of a systematic approach
1.2. The current stage of the scientific and technological revolution (NTR)
1.2.1. NTR as a system
1.2.2. Features of modern science
1.2.3. The creation of technical systems is a progressive direction in the development of technology
1.2.4. Education and its role in scientific and technical progress
1.2.5. Once again about science in general
1.2.6. Development of technical systems as an object of research, evaluation and management
1.3.1. System
1.3.2. Connection
1.3.3. Structure and structural study
1.3.4. Whole (integrity)
1.3.5. Element
1.3.6. Systems approach (SP)
1.3.7. System analysis
1.3.8. Other concepts of system analysis
Chapter 2. LOGIC AND METHODOLOGY OF SYSTEM ANALYSIS
2.1. Logical foundations of system analysis
2.2. Methodology of knowledge
2.2.1. The concept of method and methodology
2.2.2. Types of methodology and their creation
2.2.3 System analysis methods
2.2.4. Principles of system analysis
2.3. Integral type of knowledge
CHAPTER 3. THEORY AND PRACTICE OF THE IMPLEMENTATION OF SYSTEM ANALYSIS
3.1. Working stages of system analysis implementation
3.2. The cycle as the foundation of the universe
3.3. Cycle theory
3.4. PZhTs TS - the principle and object of assessment and management
3.5. The value of the complete life cycle
3.6. Organizational management structures
3.7. Some practical results of applying system analysis
CONCLUSION
INTRODUCTION
Who takes on private questions, without prior
common decisions, the one will inevitably be at every turn
unconsciously for oneself to "stumble" on these common
questions. And to blindly stumble upon them in every particular case means dooming one's policy to the worst vacillation and unscrupulousness.
“The researcher feels his ignorance the more, the more he knows...” - this paradoxical remark of the greatest physicist of our time, R. Oppenheimer, characterizes the paradoxical situation in modern science as precisely as possible. If until recently a scientist was literally chasing facts, today he is unable to cope with their flood. Analytical methods, so effective in the study of particular processes, no longer work. We need a new, more effective principle that would help to understand the logical connections between individual facts. Such a principle was found and called the principle of systemic movement or systemic approach (SP).
This principle determines not only new tasks, but also the nature of all management activities, the scientific, technical, technological and organizational improvement of which is due to the very nature of large-scale public and private production.
The diversity and the growing volume of the tasks of economic construction facing us require their mutual coordination and the provision of a common purposefulness. But this is difficult to achieve if one does not take into account the complex dependence between individual regions of the country, between branches of the national economy, and between all spheres of the country's social life. More specifically, 40% of the information a specialist needs to draw from related areas, and sometimes remote ones.
Already today, a systematic approach is used in all areas of knowledge, although in its various areas it manifests itself in different ways.
So, in technical sciences we are talking about systems engineering, in cybernetics - about control systems, in biology - about biosystems and their structural levels, in sociology - about the possibilities of a structural-functional approach, in medicine - about the systemic treatment of complex diseases (collagenoses, systemic vasculitis etc.) by general practitioners (systemic doctors).
In the very nature of science lies the desire for unity and synthesis of knowledge. The study of this desire, the identification of the features of this process is one of the tasks of modern research in the field of the theory of scientific knowledge. In modern science and technology, due to their extraordinary differentiation and saturation with information, the problem of conceptual synthesis is of particular importance. Philosophical analysis of the nature of scientific knowledge involves consideration of its structure, which allows us to identify ways and means of unity and synthesis of knowledge, leading to the formation of new concepts, to conceptual synthesis. By studying the processes of unification and synthesis of scientific theories in the field of developing sciences, one can identify their various types and forms. In our initial approach to the problem, we see no difference between the unity of knowledge and its synthesis. We only note that the concept of the unity of knowledge presupposes a certain division of it, its structure. The synthesis of knowledge, understandable as the process of the birth of a new one, arises on the basis of certain types of association or interaction of its structural forms. In other words, the unity and synthesis of knowledge are only certain stages in the development of science. Among the variety of forms of unification of knowledge leading to synthesis, it is easy to see four different types, in other words, four types of unity of scientific knowledge.
The first type of unification consists in the fact that in the process of differentiation of knowledge, scientific disciplines arise, similar to cybernetics, semiotics, general systems theory, the content of which is associated with the identification of common features in the most diverse areas of research. On this path, a kind of integration of knowledge takes place, which to some extent compensates for the diversity and delimitation of various scientific disciplines from each other. It is well known that new knowledge is synthesized along this path.
Considering this integration in more detail, we can observe the second type of unity of scientific knowledge. Studying the genesis of scientific ideas, we notice a tendency towards methodological unity. This trend consists in the methodological continuation of one special science, i.e., in the transfer of its theory to other areas of research. This second path to the unity of knowledge can be called methodological expansion. Let us immediately note that this expansion, fruitful at a certain stage, sooner or later reveals its limits.
The third type of striving for the unity of scientific knowledge is associated with fundamental concepts that initially arise in the field of natural language and are then included in the system of philosophical categories. Concepts of this kind, through appropriate refinements, acquire the meaning of the original concepts of emerging scientific theories. We can say that in this case we are dealing with a conceptual form of the unity of science.
The consistent development of the conceptual unity of science creates the prerequisites for the fourth and, in a certain sense, the most essential path to the unity and synthesis of scientific knowledge, namely, the path of developing and using a unified philosophical methodology. Science is a system of diverse knowledge, and the development of each element of this system is impossible without their interaction. Philosophy explores the principles of this interaction and thereby contributes to the unification of knowledge. It provides the basis for a higher synthesis, without which the synthesis of scientific knowledge at its more specialized levels of research is impossible (Ovchinnikov unity and synthesis of scientific knowledge in the light of Lenin's ideas // Vopr. filos. 1969. No. 10).
Other approaches to the problem of the unity and synthesis of knowledge are also possible. But one way or another, this problem needs, as a prerequisite for research, a certain interpretation of the nature of science. And it is systemic, just like the world around us, our knowledge and all human practice. Therefore, the study of these objects should be carried out using methods that are adequate to their nature, i.e., systemic!
The system nature of the world is represented as an objectively existing hierarchy of variously organized interacting systems. Systematic thinking is realized in the fact that knowledge is presented as a hierarchical system of interrelated models. Although people are part of nature, human thinking has a certain independence in relation to the surrounding world: mental structures are not at all obliged to obey the limitations of the world of real structures. However, when entering into practice, comparison and coordination of the systems of the world and thinking are inevitable.
Practical coordination goes through the practice of cognition (convergence of models with reality) and the practice of transforming the world (approximation of reality to models). The generalization of this experience led to the discovery of dialectics; following its laws is a necessary condition for the correctness of our knowledge, the adequacy of our models. Modern system analysis proceeds in its methodology from dialectics. We can express ourselves more definitely and say that system analysis is applied dialectics. With the advent of systems analysis, philosophy has ceased to be the only theoretical discipline that has no applied analogue. On the practical side, applied systems analysis is a technique and practice of improving intervention in real problem situations.
Firstly, an important stage in the study of real situations and the construction of their models (of different levels - from verbal to mathematical) is common to all specialties. For this stage, system analysis offers a detailed methodology, the mastery of which should become an important element in the training of specialists of any (not only technical, but also natural and humanitarian) profile.
Secondly, for some engineering specialties, primarily related to the design of complex systems, as well as for applied mathematics, systems analysis will obviously become one of the major courses in the near future.
Thirdly, the practice of applied system analysis in a number of countries convincingly shows that such activity has become a profession for many specialists in recent years, and some universities in developed countries have already started graduating such specialists.
Fourth, an extremely favorable audience for teaching systems analysis is advanced training courses for specialists who have worked in industry for several years after graduation and have experienced first hand how difficult it is to deal with real life problems.
The introduction of system analysis into university curricula and the educational process is associated with overcoming some difficulties. The main ones are the predominance of the technocratic approach in engineering education, the traditionally analytical construction of our knowledge, specialties, reflected in the disciplinary organization of faculties and departments, the lack of educational literature, the unawareness by existing firms of the need to have professional systems engineers in their staffs, so it seems that such specialists should be trained not for anyone. The latter is not accidental, because, according to sociological surveys, only 2-8% of the population owns (spontaneous) system analysis.
However, life takes its toll. The sharply increased requirements for the quality of training of specialists graduating from higher education, the need for an interdisciplinary approach to solving complex issues, the growing depth and scale of problems with limited time and resources allocated to their solution - all these are significant factors that will make the teaching of system analysis necessary, moreover , inevitable (Tarasenko F. Introduction to the article by R. Akoff “Mismatch between the education system and the requirements for successful management // Vestn. Vyssh. Shk. 1990. No. 2). And the psychological inertia that has always stood in the way of innovation can only be overcome by propagating new ideas, by acquainting the broad pedagogical, scientific and student community with the essence of the new, which is making its way. Let's hope that the proposed manual will play its role in drawing the attention of students and teachers to some features of system analysis. Moreover, system analysis is promising for the harmonious development of the individual, for the student to get an idea of the scientific picture of the world (SCM) as a holistic assimilation of knowledge on the basics of science, and for the formation of a scientific worldview, and for understanding knowledge! It is misunderstanding that leads to the loss of the desire of many to study, the loss of the prestige of higher education.
Summarizing the above, we can make a firm conclusion about the need to introduce the discipline "system analysis" into modern education - both in the form of one of the general courses in the fundamental training of students and listeners, and in the form of a new specialty that so far exists only in a few universities in the world, but, undoubtedly very promising.
The study of system analysis is proposed to begin with the familiarization of the reference signals (by). Why? The whole world around us has a systemic (nonlinear) nature. Therefore, its constituent objects, phenomena and processes must objectively reflect its realities, i.e., they must also be systemic, non-linear. However, the modern system (what a paradox in the name!) of higher education is built on a linear principle - and this is its essential drawback. It can be eliminated gradually, through the transition from linear to non-linear forms. There are many ways of this movement. One of them is the development and study of reference signals, which are a non-linear text (hypertext!), for which the right hemisphere of the human brain is responsible, creating a full-blooded and natural image of the world. It is the reference signals that fix and intensify the independent work of students, including in the direction of studying and understanding system analysis.
Reference signals (OS) are a specially coded and specially designed content of a topic, section or discipline as a whole. The principles of coding are:
extracting the quintessence of the material;
presentation of the material in the most convenient form for studying.
Reference Signals for Studying System Analysis
1. The reduction of many to one is the fundamental principle of beauty.(Pythagoras, ancient Greek scientist, professor).
2. The depth of insight and the elegance of a hypothesis are almost always a consequence of the generality(V. Druzhinin, professor; D. Kontorov, professor).
4. Those who linger only on the “details” of knowledge acquire the “seal of spiritual misery”(Julien Offret Lamerty, French philosopher and physician, representative of French materialism).
5. ...Different things become quantitatively comparable only after they are reduced to the same unity. Only as expressions of the same unity are they eponymous, and therefore comparable quantities.(K. Marx, F. Engels, German philosophers).
6. In the not too distant future society will have "one science". Its representatives are not superuniversals, all knowing and all able. These will be highly educated, erudite people who have a deep understanding of the development of science and society as a whole, who know the main ways and possibilities of cognition through “oneself” (man) of all nature. At the same time, they will be generalists in one or a group of industries.(K. Marx).
7. The unity of nature is found in the striking similarity of differential equations relating to different areas of phenomena(- the founder of the Soviet state).
8. Facts in science and technology, if taken in in general, in their connection, not only a “stubborn”, but also an unconditionally conclusive thing ... It is necessary to take not individual facts, but the entire set of facts related to the issue under consideration, without a single exception. We will never achieve this completely, but the demand for comprehensiveness will warn us against mistakes and from "death"().
9. Who takes on particular questions, without first solving the general ones, he will inevitably, at every step, unconsciously for himself, "stumble" on these general questions. And to stumble blindly on them in each particular case- means dooming your politics on the the worst vacillation and unscrupulousness().
10. Science is a whole. Its division into separate areas is due not so much to the nature of objects as to the limited abilities of human cognition. In fact, “there is an unbroken chain from physics to chemistry, through biology and anthropology to the social sciences, a chain which in no place can be torn apart, except at will.(my discharge. - W. C.) (M. Planck, German physicist, Nobel Prize winner).
11. The goal of modern science is reveal the internal connection and trends, discover the laws, the objective logic of these changes().
12. The goal of modern science is to see the general in the particular and the permanent in the transient.(C. Whitehead, Canadian professor).
13. ...We need a comprehensive, systematic approach to making responsible decisions. We have adopted such a weapon and will consistently implement it.(, General Secretary of the Central Committee of the CPSU).
14. Science has seriously enriched the theoretical arsenal of planning by developing methods of economic and mathematical modeling, system analysis, etc. It is necessary to use these methods more widely ... This makes it important not only to produce the appropriate equipment, but also to train a significant number of qualified personnel (A. I. Brezhnev).
15. Among the most pressing problems in the development of modern science, one of the first places is occupied by the integration of scientific knowledge. It finds its expression in the development of general concepts, principles, theories, concepts in creating a common(my discharge. - W. C.) pictures of the world. The turbulent process of the emergence of general theories of certain types of knowledge is primarily due to the interests of increasing their effectiveness and the ability to consolidate them.(V. Turchenko, philosopher).
16. The synthesis of various sciences proved to be extremely fruitful. This trend is becoming more important, because the largest discoveries of our time are made at the junctions of various sciences, where new scientific disciplines and directions were born.(, philosopher).
17. The process of integration leads to the conclusion that many problems will receive correct scientific coverage only if they are based simultaneously on the social, natural and technical sciences. This requires the application of the results of research by various specialists - philosophers, sociologists, psychologists, economists, engineers ... It was in connection with the integration processes that the need arose for the development of systemic research(, philosopher).
18. The method of a holistic approach is essential in the development of a higher level of thinking, namely transition from the analytical stage to the synthetic, which directs the cognitive process to a more comprehensive and deep(my discharge. - V.S.) knowledge of phenomena (, philosopher; , philosopher).
19. The main goal of any science is to to reduce the most surprising to the ordinary, to show that complexity, if look at it from the right angle, it turns out to be only masked(my discharge. - V.S.) simplicity to discover patterns hidden in apparent chaos. But these patterns can be very complex in their representation or contain such initial data that are not enough to carry out any calculation.(E. Quaid, American systems engineer).
20. Thinking the activity of an individual Person is the more productive and logical, the more fully and deeply he has mastered the universal(my discharge. - V.S.) categories of thinking (, professor).
21. In nature does not have separately existing equipment and technology, physics and biology, research and design(M. Plank).
22. Natural phenomena are usually complex. They don't know anything about how we divided our knowledge into sciences. Only a comprehensive consideration of phenomena from the point of view of physics, chemistry, mechanics, and sometimes biology will make it possible to recognize their essence and apply them in practice.(, academician).
23. The scientific and technological revolution has revealed a number of intellectual "diseases". One of them is the narrowness of professional consciousness. In any area of scientific and technological activity, nothing significant can be done if attention and efforts are focused on a bottleneck. Narrowing the search is a condition of a seemingly competent solution to the problem. But the constant participation of specialists in such programs often leads to the fact that they lose a panoramic vision of the entire front of work. There is a "deafness of specialization", which, under unfavorable conditions, can develop into a "disease", called by K. Marx "professional cretinism". It is no coincidence that it was he who laid down the principles of the joint venture in the analysis of capitalist production. His "Capital" is the first fundamental systematic study of the structure of society(E. Zharikov, professor).
24. Systemic approach to phenomena is one of the most important intellectual properties of a person(, Professor).
25. To understand the essence of life
And describe exactly
He dismembered the body
BUT driving the soul away
Looking at parts. But...
Their spiritual connection
Disappeared, irretrievably gone!
G. Goethe, German poet
See eternity in an instant
A huge world - in a grain of sand,
In a single handful - infinity
And the sky - in a cup of a flower.
W. Blake, English philosopher and poet
26. A scientific approach means a systematic one!!!().
27. The world, our knowledge and all human practice has a systemic nature. Information comes from the outside world. We are thinking. It is necessary to harmonize the system and thinking. But thinking is provided by education. Therefore, it must be systemic!().
28. The prestige of engineering creativity was undermined, the world-famous domestic schools of technology developers were confused. A vicious philosophy of imitation and mediocrity has developed. As a result, some of the products do not meet the current level of science and technology. What are ... the roots of the current situation with the technical level of the machines being created? First of all, in the fact that, in essence, we still lacked a systematic analysis of the latest world achievements.(chev, General Secretary of the Central Committee of the CPSU).
29. I think that higher education is also to blame for this, not preparing appropriate specialists. In the editorial "On the Ways of Restructuring Higher Education"(Bulletin of Higher School. 1986. No. 7) noted what"...now for the first time solutions based on system positions were proposed().
30. An important stage of systematic research of real situations and the construction of their models is common to almost all specialties;
for engineering professionals associated with the design of STS, also for applied mathematics systems analysis in the near future(what to expect, and so late. - V.S.) obviously, will become one of the major courses;
the practice of applied SA in a number of countries convincingly shows that such scientific and technical activity (S&T) has become a profession for many specialists in recent years, and several universities in developed countries have already started graduating such specialists;
An extremely favorable audience for teaching SA is the IPC of specialists who have worked in industry for several years after graduation and have experienced first hand how difficult it is to deal with real life problems(, Professor).
Difficulties in introducing SA into the learning process: the traditionally analytical construction of our knowledge and specialties, reflected in the organization of faculties and departments. Therefore, leaders do not know the essence of SA! Report at Leningrad State University: "Who Thinks Systemically?" Answer: 8% of the leaders of the North-West().
31. What is the importance of SA? First of all - to make optimal decisions(del). Half of the world's anxiety (and therefore disease) comes from people trying to make decisions without knowing enough about what the decision is based on. The solution should not be any, but optimal. But it is impossible to make an optimal decision within the framework of subject knowledge!(A. Rapoport, Canadian professor).
32. I am not aware of any completed systems research in engineering(, academician).
33. Modern systems research, unfortunately, remains either private scientific developments or is concentrated around formal methodological issues.(, Professor).
34. Except in isolated cases, it must be recognized that the systems methodology is rarely used on a massive scale and for most developments ... the empirical development of the trial and error method is characteristic(ditch, academician).
35. Systemic the approach is easily proclaimed in a general way, but it is very difficult to implement it in a specific form, since a multi-aspect orientation requires special scientific, organizational, technical, pedagogical training, and other conditions in conjunction with targeted measures to provide resource support for systemic activities. We emphasize that a single and continuous systemic activity, starting from the study of a specific object and ending with the liquidation that occurs after its physical or moral obsolescence().
36. SA is characterized mainly not by a specific scientific apparatus, but by an orderly(my discharge. - W. C.), logically justified approach to the study of the problem and the use of appropriate methods for solving them, which can be developed within the framework of other sciences(, Professor).
37. If natural science was predominantly a collecting science, now it has become in essence an ordering science.(my discharge. - V.S.) science, science about connections(F. Engels).
38. We all... use a huge store of unconscious knowledge, skills and abilities that have been formed over the long evolution of mankind(, academician). In this regard, the question arises - how can we read this unconscious knowledge to students, especially aiming them at independent work?().
39. Most specialists understand (synthesis) not directly, but in zigzags, not consciously, but spontaneously, go towards it, not seeing clearly their ultimate goal, but groping closer to it, staggering, sometimes even backwards().
40. With principle development(element SA. - V.S.) everyone agrees. But this is a superficial agreement by which truth is stifled and vulgarized.().
41. Today, a systematic approach is spoken of in almost all sciences, although in its various sections it manifests itself in different ways. So, in technical sciences, we are talking about systems engineering, in cybernetics - about SU, in biology - about biosystems and their structural levels, in sociology - about the possibilities of a structural-functional approach, in medicine - about complex systemic diseases (collagenoses, systemic vasculitis, etc.). .), which should be treated by general practitioners (systemic doctors)(, academician).
42. The essence of the systems approach is vividly expressed in one statement attributed to an English officer during the Second World War: "These guys will not even pick up a soldering iron until they thoroughly understand the strategy of military operations in the entire Pacific theater." The integrity of local and global tasks of a specific activity is evident!().
43. The value of consistency: for making optimal (!) decisions that cannot be made in subject knowledge; otherwise- bungling and incompetence; to reduce the load on memory; overloads in high school arise due to too much mobilization of students' memory with a pronounced underload of their thoughts, imagination and fantasy; practice: increases students' interest in science; not only develops students, but also educates them; the perception of theoretical knowledge occurs in whole blocks; SA - a prerequisite for further rational mastery of knowledge; as soon as the student is aware of the nature of knowledge, the ways of obtaining and fixing it, the composition and structure of scientific theory, then he will be able to comprehend new knowledge according to the model learned at the university through the SA course; the attitude to comprehend knowledge in a certain structure leads the student to the formulation of questions to which he must seek answers in different sources, to a critical examination of new information; all these are necessary elements of creative thinking; for understanding, because it is precisely this that is the result of synthesis, not analysis; consistency allows you to get HKM- holistic assimilation of knowledge on the basics of science.
After all, science is a whole and its division into separate areas is conditional. NKM is a model, image of reality, which is based on the data of specific sciences about nature and society. Knowledge related to NCM is called ideological: it is formed very slowly, but SA accelerates its formation.().
CHAPTER 1. THE NEED TO APPEAR
OF SYSTEM ANALYSIS, ITS ESSENCE
AND TERMINOLOGY
The reduction of many to one is the fundamental principle of beauty.
Pythagoras
History is the science of the past and the science of the future.
L. Febvre
1.1. History of the development of a systematic approach
The components of the concepts of "system analysis", "system problem", "system research" is the word "system", which appeared in Ancient Hellas 2000-2500 years ago and originally meant: combination, organism, device, organization, system, union. It also expressed certain acts of activity and their results (something put together; something put in order).
The word "system" was originally associated With forms of socio-historical existence. Only later the principle of order, the idea of ordering are transferred to the Universe.
The transfer of the meaning of a word from one object to another and, at the same time, the transformation of a word into a generalized concept are carried out in stages. The metaphorization of the word "system" was started by Democritus (460-360 BC), an ancient Greek philosopher, one of the founders of materialistic atomism. He likens the formation of complex bodies from atoms to the formation of words from syllables and syllables from letters. Comparison of indivisible forms (elements with letters) is one of the first stages in the formation of a scientific and philosophical concept that has a generalized universal meaning.
At the next stage, further universalization of the meaning of the word takes place, endowing it with a higher generalized meaning, which makes it possible to apply it to both physical and artificial objects. Universalization can be carried out in two ways - either in the process of myth-making, i.e., building a myth on the basis of a metaphor [characteristic of one of the founders of objective idealism Plato (427-347 BC)], or by recreating a philosophical-rational picture of the universe and human culture, i.e., the transformation and deployment of metaphor in the philosophical system [characteristic of Aristo-322 BC. e.), oscillating between materialism and idealism] [“Stages in the interpretation of the systematic nature of scientific knowledge (antiquity and modern times)”. System Research // Yearbook. M.: Nauka, 1974].
So, in ancient (ancient) philosophy, the term "system" characterized the orderliness and integrity of natural objects, and the term "syntagma" - the orderliness and integrity of artificial objects, primarily products of cognitive activity. It was during this period that the thesis was formulated that the whole is greater than the sum of its parts (Philosophical Dictionary. M .: Politizdat, 1980).
Without touching on the question of the interpretation of the systemic nature of knowledge in medieval philosophy, we only note that new terms began to be used here to express the integrativity of cognitive formations: sum, discipline, doctrine...
With the emergence of science and philosophy of the Renaissance (XV century), a radical transformation in the interpretation of being is associated. The interpretation of being as a cosmos is replaced by its consideration as a system of the world. At the same time, the system of the world is understood as independent of a person, having its own type of organization, hierarchy, immanent (proper, inherent in any object, phenomenon, arising from their nature) laws and sovereign structure. In addition, being becomes not only the subject of philosophical reflection, seeking to comprehend its integrity, but also the subject of socio-scientific analysis. A number of scientific disciplines arise, each of which singles out a certain area in the natural world and analyzes it with the methods characteristic of these disciplines.
Astronomy was one of the first sciences that moved to the ontological-naturalistic interpretation of the systemic nature of the universe. The discovery of N. Copernicus (1473-1543) played a big role in the formation of a new interpretation of the systemic nature of being. He created the Heliocentric system of the world, explaining that the Earth, like other planets, revolves around the Sun and, in addition, rotates around its axis. Teleologism, which weighed down the ideas of Copernicus, was later overcome by G. Galileo (1564-1642) and I. Newton (1642-1727).
M The methodological basis for the preparation and justification of decisions on complex problems of a scientific, economic and technical nature is a system analysis.
The term "systems analysis" first appeared in connection with the tasks of military command in the research of the RAND Corporation (1948). The first book on systems analysis was published in 1956 by American scientists Kahn and Mann. In domestic literature, this term became widespread only after it was published in 1969 by the Sov. Radio” book by L. Optner “System Analysis for Solving Business and Industrial Problems”.
The attraction of this methodology is due, first of all, to the fact that when searching for solutions to a problem, one has to make a choice in conditions of uncertainty caused by the presence of factors that cannot be rigorously quantified.
In the general formulation of the question, system analysis can be defined as follows.
Definition 4.2. System analysis is a scientific direction that provides, on the basis of a systematic approach, the development of methods and procedures for solving semi-structured problems in the presence of significant uncertainty.
At present, system analysis already contains a wide range of various methods that can be grouped into the following groups:
· heuristic programming;
· semiotic approach;
· analogy methods;
· analytical methods;
· simulation modeling.
The existing methods of mathematical analysis, which have justified themselves in relatively simple cases, usually turn out to be ineffective in the study of complex systems. In this regard, heuristic programming methods based on the principle of analyzing human activity have become widespread.
Table 5.1
Among the methods of this group, a significant role is played by the methods of expert assessments (the method of brainstorming and exchange of opinions, the Delphi method, and others), using one form or another of generalizing the totality of subjective ideas of a certain group of specialists (experts) on the problem under study. The advantage of this method is a certain simplicity and accessibility.
The main drawback is that most often it is not possible to establish the degree of reliability of the examination.
A common drawback of heuristic programming is the lack of formal rules for finding "heuristics". The search for heuristics is more of an art and does not always lead to a positive result.
Heuristic methods are closely related to the methods of the semiotic approach, based on the possibilities of the expressive means of natural language, which allow one to describe a wide class of objects, processes and phenomena very effectively and under certain agreements.
One of the methods that implement the semiotic approach is situational management.
This method is based on the following principles.
1. The model of the control object and the description of the processes occurring in it is semiotic and is built on the basis of texts expressed in natural language. The situation description model is also semiotic based on natural language.
2. The formation of the model of the control object and the processes occurring in it occurs either by creating it by a specialist before entering it into the computer, or on the basis of an analysis of the behavior of the object in various situations, carried out by the computer itself. In the latter case, the computer must contain some mechanisms for carrying out such an analysis.
The general model includes:
· zero level, where many basic concepts are stored;
· the first level containing instant photos of the real situation;
· the second level, where regular connections between objects of the outside world are displayed, etc.
The second level model is still very detailed and describes the outside world in too small units. All subsequent layers of the model, starting from the third level, carry out gradual generalizations. In these generalizations, the role of the components between which a connection is established is played by structures identified in models that lie in smaller layers.
Thus, the whole model is conceived as a set of a number of models, ranging from models of direct recognition at the first level to the model of abstract concept formation.
Currently, system analysis (SA) is the most constructive direction. This term is used ambiguously. But in any case, they always assume research methodology, an attempt is made to identify the stages of research and propose a methodology for performing these stages in specific conditions. Thus, the following definitions can be given for system analysis.
System analysis in a broad sense-this is a methodology for setting and solving problems of building and researching systems, closely related to mathematical modeling.
In a narrow sense, system analysis-methodology for formalizing complex (hard to formalize, poorly structured) tasks.
System analysis- this is a purposeful creative activity of a person, on the basis of which a representation of the object under study is formed in the form of a system.
System analysis is characterized not by the use of new physical phenomena and not by a specific mathematical apparatus, but by an ordered and logically justified approach to solving a problem. It serves as a way to streamline and effectively use the knowledge, experience and even intuition of specialists in the process of setting goals and making decisions on emerging problems.
System analysis arose as a generalization of the techniques accumulated in the problems of operations research and control in technology, economics, and military affairs. Appropriate methods and models were borrowed from mathematical statistics, mathematical programming, game theory, queuing theory, automatic control theory. The foundation of these disciplines is systems theory.
Definition 4.3. Systems analysis is a methodology for solving large problems based on the concept of systems.
Definition 4.4. System analysis in a broad sense– this is a methodology (a set of methodological techniques) for posing and solving problems of building and studying systems, closely related to mathematical modeling.
Definition 4.5. System analysis in the narrow sense– it is a methodology for formalizing complex (hard to formalize, poorly structured) tasks.
Systems analysis (SA) arose as a generalization of the techniques accumulated in the problems of operations research and control in technology, economics, and military affairs. Appropriate methods and models were borrowed from mathematical statistics, mathematical programming, game theory, queuing theory, automatic control theory. The foundation of these disciplines is systems theory.
System analysis is a purposeful creative activity of a person, on the basis of which a representation of the object under study is formed in the form of a system.
System analysis is characterized by an ordered composition of methodological research openings.
System analysis is a constructive direction containing a methodology for dividing processes into stages and sub-stages, systems into subsystems, goals into subgoals, etc.
SA has developed a certain sequence of actions (stages) in setting and solving problems, which is called method of system analysis. This technique helps to set and solve applied problems more meaningfully and competently. If at some stage there are difficulties, then you need to return to one of the previous stages and change (modify) it. If this does not help, then the task turned out to be too complicated and it needs to be divided into several simple subtasks, i.e. perform decomposition. Each of the obtained subtasks is solved by the same method.
At the same time, system analysis has its own specific purpose, content and purpose.
At the heart of the system analysis methodology is the operation of a quantitative comparison of alternatives, which is performed in order to select an alternative to be implemented. If the requirement of different quality of alternatives is met, then quantitative estimates can be obtained. But in order for quantitative estimates to allow comparison of alternatives, they must reflect the properties of the alternatives involved in the comparison (output, efficiency, cost, and others).
In systems analysis, problem solving is defined as an activity that maintains or improves the performance of a system. Techniques and methods of system analysis are aimed to put forward alternative solutions to the problem, identify the extent of uncertainty for each option and compare options for their effectiveness.
The purpose of system analysis is to streamline the sequence of actions in solving major problems, based on a systematic approach. Systems analysis is designed to solve a class of problems that is outside the short range of daily activity.
The main content of system analysis lies not in a formal mathematical apparatus that describes “systems” and “problem solving” and not in special mathematical methods, for example, uncertainty assessments, but in its conceptual, i.e. conceptual, apparatus, in its ideas, approach and attitudes.
Systems analysis as a methodology for solving problems claims to play the role of a framework that combines all the necessary knowledge, methods and actions to solve a problem. This is what determines his attitude to such areas as operations research, statistical decision theory, organization theory, and others like it.
The system is thus what solves the problem.
Definition 4.6. P A problem is a situation characterized by a difference between a necessary (desired) output and an existing output.
An exit is necessary if its absence poses a threat to the existence or development of the system. The existing output is provided by the existing system. The desired output is provided by the desired system.
Definition 4.7. Problem– it is the difference between the existing system and the desired system.
The problem may be to prevent a reduction in yield, or it may be to increase yield. The conditions of the problem represent the existing system (the "known"). The requirements represent the desired system.
Definition 4.8 . Solution there is something that fills the gap between the existing and the desired systems.
Therefore, the system that fills the gap is an object of construction and is calleddecision Problems.
Pproblem characterized by the unknown contained in it and the condition. Maybe one or many areas of the unknown. The unknown can be determinedqualitatively, but notquantitatively. A quantitative characteristic can be a range of estimates representing the supposed state of the unknown. It is significant that the definition of one unknown in terms of another may be contradictory or redundant.
The unknowns can only be expressed in terms of the known, i.e. such, objects, properties and connections of which are established.
PThereforefamousdefined as a quantity whose value is set. The existing state (the existing system) can contain both the known and the unknown; this means that the existence of an unknown may not interfere with the system's ability to function. The existing system is, by definition, logical, but may not satisfy the constraint. Thus, system performance alone is not the ultimate criterion for good, as some perfectly functioning systems may fail to achieve goals.
The definition of goals can only be given in terms of system requirements .
System requirements are a means of capturing unambiguous statements that define a goal. While requirements for systems are stated in terms of objects, properties, and relationships, goals can be defined in terms of a desired state. The goals and desired state for a given set of system requirements may be exactly the same. If they are different, then the requirements are said to represent the desired system. In general, goals are identified with the desired system.
Definition 4.9. P The gap between the existing system and the desired system constitutes what is called a problem.
The purpose of the actions is to minimize the gap between the existing and the proposed system. Maintaining or improving the state of the system is identified with the gap between the existing state and the desired state.
When solving the problems of the business and industrial world, the most important points are objectivity and consistency.
The body of knowledge widely confirmed by observation becomes evidence .
Definition 4.10. Observation is a process by which data is identified with a system for the subsequent explanation of that system.
The process of explanation must be rational, that is, carried out logically.
Definition 4.11.Preservation of the existing state is the ability to keep the output of the system within prescribed limits.
Definition 4.12.Improving the state of a system is the ability to achieve an output above or beyond that obtained in the existing state.
Objectivity is a basic observation requirement.
Definition 4.13.Rationality (logicality) is a process of thinking based on the use of logical inference.
P The process of finding a solution to a problem centers around the iteratively performed operations of identifying the condition, as well as the purpose and possibilities for solving it. The result of identification is a description of the condition, purpose and possibilities in terms of system objects (input, process, output, feedbacks and restrictions), properties and relationships, i.e. in terms of structures and their constituent elements.
Every input of a system is an output of this or another system, and every output is an input.
To select a system in the real world means to indicate all the processes that give a given output.
Artificial systems these are those whose elements are made by people, that is, they are the output of consciously performed human processes.
In any artificial system, there are three different sub-processes in their role: core process, feedback and constraint.
Definition 4.14.FROM property of this process is the ability to translate a given input into a given output .
Connection defines the sequence of processes, i.e., that the output of some process is the input of a certain process.
Main process converts input to output.
Feedback performs a number of operations:
· compares the output sample with the output model and highlights the difference;
· evaluates the content and meaning of the difference;
· develops a solution articulated with difference;
· forms the decision input process (intervention in the process of the system) and influences the process in order to bring the output and the output model closer together.
Restriction process excited by the output consumer of the system, analyzing its output. This process affects the output and control of the system, ensuring that the output of the system is consistent with the goals of the consumer. The system constraint adopted as a result of the constraint process is reflected by the output model. The limitation of the system consists of the purpose (function) of the system and forcing connections (qualities of the function). Coercive ties must be compatible with the goal.
E If the structures, elements, conditions, goals and possibilities are known, the detection of the problem (identification) has the character of determining quantitative relations, and the problem is called quantitative.
If the structure, elements, conditions, goals and opportunities are known in part, the identification is qualitative, and the problem is called quality or loosely structured.
As a problem solving methodology system analysis indicates a fundamentally necessary sequence of interrelated operations, which (in the most general terms) consists of identifying a problem, designing a solution, and implementing that 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 (the so-called 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 system methodology.
reduction (reduction) in the number of variables is based on the analysis of the sensitivity of the problem to changes in individual variables or groups of variables, aggregation of variables into summary factors, selection of appropriate forms of criteria, and also application, where possible, of mathematical methods for reducing enumeration (methods of mathematical programming, etc.). .).
Logical integrity process is provided by explicit or implicit assumptions, each of which can be a source of risk. We note once again that the structure of system functions and problem solutions in system analysis is postulated, i.e., they are standard for any systems and any problems. Only the methods of executing 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 part will determine unforeseen opportunities and limitations that can become a source of future problems.
T These are, in general terms, the main ideas of systems analysis as a problem-solving methodology.
The application of system analysis in practice can occur in two situations:
· starting point is the appearance new problem;
· the starting point is a new possibility found outside of direct connection with the given range of problems.
Note that the definition of an exact list of particular functions that ensure the implementation of the listed stages of solving a new problem is the subject of independent research, the need and importance of which cannot be overestimated.
The solution of the problem in the situation of a new problem is carried out according to the following main stages:
1. detection of a problem (identification of symptoms);
2. assessment of its relevance;
3. definition of purpose and coercive links;
4. definition of criteria;
5. opening the structure of the existing system;
6. identification of defective elements of the existing system, limiting the receipt of a given output;
7. assessment of the weight of the influence of defective elements on the system outputs determined by the criteria;
8. definition of a structure for building a set of alternatives;
9. evaluation of alternatives and selection of alternatives for implementation;
10. definition of the implementation process;
11. coordination of the found solution;
12. implementation of the solution;
13. evaluation of the results of implementation and the consequences of solving the problem.
Implementation of the new feature takes a different path.
The use of this opportunity in a given area depends on the presence in it or in related areas of an actual problem that needs such an opportunity for its solution. Exploiting opportunities in the absence of problems can be, at the very least, a waste of resources.
Exploiting opportunities when there are problems, but ignoring problems as an end in itself, can deepen and exacerbate the problem.
The development of science and technology leads to the fact that the emergence of a new opportunity situation becomes an ordinary phenomenon. This requires a serious analysis of the situation when a new opportunity arises. A capability is disposed of if the best alternative includes that capability. Otherwise, the opportunity may remain unused.
One of the challenges in using systems analysis methodology to solve a problem is to isolate useful, valuable elements of the heuristic process and apply them in conjunction with the methodology. Thus, the challenge is to introduce structure into a semi-structured process.
In doing so, at least the following basic requirements must be met:
1) the process of solving the problem should be depicted using flow diagrams (sequence or process structure) indicating the points of principal decisions;
2) the stages of the process of finding fundamental solutions should be described in detail;
3) the main alternatives and how to obtain them must be demonstrable;
4) the assumptions made for each alternative must be determined;
5) the criterion by which judgments are made about each alternative must be fully defined;
6) the detailed presentation of the data, the relationship between the data and the procedures by which the data are to be evaluated, should be part of any decision;
7) the most important alternative solutions and the arguments necessary to explain the reasons for the exclusion of rejected solutions must be shown.
These requirements are not equal in importance, precision of expression, or degree of completeness and objectivity. Each requirement has its own value.
O However, based on the content of the mentioned stages of solving a new problem, the following methods can be used: the theory of search and discovery, the theory of pattern recognition, statistics (in particular, factor analysis), the theory of experiment, operations research and related models (queues, stocks, game situations and etc.), theories of behavior (homeostatic, dynamic, self-organization and others), theories of classification and ordering, the synthesis of complex dynamic systems, the theory of potential reachability, the theory of autoregulation, forecasting, engineering and cognitive psychology, artificial intelligence and knowledge engineering and related disciplines , organization theory, social psychology and sociology.
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