This task already mentioned in the previous lecture. Given its exceptional importance, let's consider it in more detail.

The degree of experience of the decision maker is largely characterized by the ability to correctly predict the situation and find the best way problem solving.

At the same time, to correctly determine the mechanism of the situation means to quickly establish the leading factors, and the ability of the decision maker to generate new, non-standard solutions is generally identified in the minds of people with art. In this regard, it is clear that the task of forming the initial set of alternatives cannot be fully formalized. The solution to this problem is creative process, in which the main role, of course, belongs to the decision maker. The emergence of this problem theoretical object research is a direct consequence of the use of the systemic principle of the plurality of alternatives in the TPR.

Before solving the problem of forming the initial set of alternatives, it is necessary to determine the system requirements that this set must meet. First, the set of alternatives should be as complete as possible. In the future, this will provide the necessary freedom of choice for decision makers and will minimize the possibility of missing out on the “best” solution. However, this first fundamental requirement is in conflict with the second, arising from the principle of matching the solution to the time, place and capabilities of the decision maker. Most often, in practice, such compliance is understood as a requirement to develop a solution in as soon as possible. Therefore, secondly, the initial set of alternatives should be visible, narrow enough so that the decision maker has enough time to assess the consequences and preference of alternatives under the existing resource constraints. The problem of meeting these two conflicting requirements is solved systematically, based on the principle of decomposition.

Following the systemic principle of decomposition, at first a set of alternatives is formed, all elements of which potentially, according to their appearance, according to the possibilities hidden in them, ensure the achievement of the target result in the current situation. The set of applicants for the method of solving the problem obtained in this way will be called the set of target alternatives.

Then, from the set of target alternatives, those options are selected that are logically consistent and can be implemented within the time allotted for the operation. In addition, the selected alternatives must be satisfied with the necessary active resources and meet common system preferences of the DM.

We will call these options selected from the target alternatives physically realizable alternatives from among the target ones. The remaining options, potentially leading to the goal, but physically unrealizable, are discarded.

The options obtained as a result of such manipulations are complemented by methods of action that give the alternatives the necessary flexibility and stability in relation to the changing or currently unknown components of the operation conditions.

As a result, they get the original set of alternatives.

Technologically, the method of forming the initial set of alternatives involves a number of special purposeful modifications of the main factors of the situation mechanism. They consist in the simultaneous or sequential impact on the controlled (subject to the will of the decision maker) part of the characteristics of the quality of the active resources used, the characteristics of the conditions and methods of action.

It is this idea that underlies most of the known methods and algorithms for the formation of the initial set of alternatives.

Historically, the first to appear are empirical methods that require minimal formalization. The simplest of this class is the method based on the use of a cause-and-effect diagram. A typical modern representative of empirical methods is the CBR method (Case-Based Reasoning - "method of reasoning based on past experience").

The next class is formed by logical-heuristic procedures, where formalization is carried out at the level of managing logical relationships. As examples of the implementation of such methods are the decision tree methods and the method of morphological tables.

Typical representatives of the class of methods for generating alternatives, in which the highest degree of formalization of all stages of generation has been achieved, are the methods of network and scheduling.

A special class is formed by the methods of forming alternatives in conditions when the decision is developed by a "group decision maker", when there is a complete or partial coincidence of interests of the participants in the decision-making process, however, due to the unequal interpretation of the goals of actions, features individual perception problem situation and for other reasons, the sovereign opinions of the participants in the decision-making process need to be harmonized in common decision. Other representatives of the methods of this class are the methods of generating alternatives in the conditions of conflict and opposition of sovereign subjects involved in the operation of decision makers either of their own free will or against their will. Such situations are characteristic of economic, social, political and military conflicts. In all such situations, as a rule, reflexive methods are used to form alternatives. Such methods are characterized by an average level of formalization using simple mathematical models.

In terms of frequency of application in practice, perhaps the first place is occupied by logical-heuristic methods. They acquired this position due to their inherent visibility, simplicity and universality of the approach, the convenience of computerization of their algorithms. The essence of these methods is that at first, on the basis of a logical analysis of the purpose of the operation, a tree of goals and objectives is built. Then each subgoal or task is also detailed, and this operation continues until the decision maker becomes clear which of the known means (or in what way) to solve each particular task.

More on the topic The problem of forming the initial set of alternatives:

1. D. Formation of the initial set of alternatives, formalization of preferences and choice.

If you ask a person who is well versed in management problems, how he could characterize the degree of experience of a manager, then most often you can find the following answer: the ability to predict the situation and quickly find the best way to solve the problem. What is "the ability to predict the situation" has already been discussed in the previous paragraph. But what is the “best way to solve a problem”? How to form ways to achieve the goal of the operation in general?

The ability of decision makers to generate new, non-standard solutions is generally identified in the minds of many with art. Apparently, this is due to the fact that the task of forming the initial set of alternatives cannot be fully formalized. Since the solution of such a problem is a creative process, in the results of which the decision maker is primarily interested, the main role in this process, of course, belongs to the decision maker. However, before proposing a scientific approach to solving this very difficult problem, let's define the system requirements that many alternatives must meet.

First, the set of alternatives should be as wide as possible. In the future, this will provide the necessary freedom of choice for decision makers and will minimize the possibility of missing out on the “best” solution. But this first, fundamental requirement is in conflict with the natural restrictions on time, place and opportunities in which decision makers usually have to work. It is impossible to develop a solution indefinitely. Otherwise, there will be no time for its implementation. Therefore, most often in practice, decision makers are required to develop a solution as soon as possible. This immediately implies the second requirement for the original set of alternatives. This set should be visible, narrow enough so that the decision maker has more time to evaluate the preference of alternatives, and the performers have more time to implement the found best solution in practice. In order to satisfy these conflicting demands in a reasonable manner, art is required, and in order not to make gross mistakes, science must be involved. So, in accordance with the systemic principle of decomposition, science first recommends forming a set of alternatives, all elements of which potentially, according to their appearance, the possibilities hidden in them, ensure the achievement of the goal.

In cases of deterministic, stochastic or naturally indeterminate "mechanisms of the situation", the method of forming the initial set of alternatives involves performing fairly simple actions. To some extent, they all come down to a number of purposeful modifications of controllable factors that determine the effectiveness of the operation (Fig. 2.2.). At the same time, the decision maker explores the possibility of simultaneously influencing the “controlled” component of these factors, since it is precisely this method of control that most often leads to the emergence of positive emergent properties in future alternatives. Moreover, if the decision maker intends to influence, for example, the quality of active resources, then in this case all methods of forming alternatives are classified as so-called engineering synthesis. If, however, the factors from the classes "Conditions" and "Methods" become the object of application of the decision maker's efforts, then we will have in mind the methods of operational synthesis of solutions.

The set of options for solving the problem obtained in the course of engineering or operational synthesis will be called the set of “target alternatives”. After receiving the "target alternatives" from their set, one should select those options that are logically consistent and can be implemented within the time allotted for the operation. At the same time, the left alternatives must be necessarily satisfied both with active resources and correspond to the general system of preferences of the decision maker. We will call these selected options (from among the target ones) “physically realizable”. Thus, the remaining options that potentially lead to the goal, but are physically unrealizable, are discarded.

The obtained subset of "physically feasible alternatives" is supplemented with options that give the methods the necessary flexibility and stability in relation to possible changes in future conditions of the operation. As a result of the work done, they get exactly what we will further call the “initial set of alternatives”.

As for the technological methods for implementing the presented general methodology for the formation of the initial set of alternatives, everything here depends on which of the theoretical classes of TPR problems we encounter in a particular situation. For obvious reasons, the greatest "technological tricks" have to be applied in situations with behavioral uncertainty.

Conventionally, all methods of forming a set of alternatives can be divided into the following classes, which differ in the degree of formalization of the applied technologies:

§ empirical (causal);

§ logical and heuristic;

§ abstract-logical (mathematical);

§ reflexive.

Historically, empirical methods emerged first. At first, people noticed some common features inherent in various practical methods for solving specific problems. Then this experience was creatively generalized and turned into a set of rules on how to act in this or that case. Similar methods are still in use today. For example, the CBR (Case-Based Reasoning) machine technology is known. Its essence is that. the analyzed decision-making situation is compared in the computer memory with all similar situations known from the past. From the database, the machine selects several situations similar to the analyzed one and presents them to the decision maker.

The choice of a specific decision by the head (manager) is based on comparing the observed situation with the situation from the database and adjusting the solutions known for these situations in relation to the features of the case under consideration.

Logical-heuristic methods for generating a set of alternatives involve the gradual division of the problem or task under consideration into separate subtasks, questions, sub-operations, and so on to such elementary actions for which heuristic solutions are already known and specific technologies their execution. By the frequency of application in practice, perhaps, it is the logical-heuristic methods that occupy the first place. Typical representatives of logical-heuristic methods are the decision tree method and the method of morphological tables. They acquired this position because of their inherent visibility, simplicity and universality of the approach, the convenience of computerization of their algorithms.

Consider the technology of the decision tree method. For a holistic and unified understanding of it, we will use three basic concepts: “important circumstance”, “measurable characteristic”, “final” element. We will consider as an "important circumstance" any factor that the decision maker considers necessary to take into account in the process of working on the problem. Important circumstances, properties of objects or tasks that can not only be described verbally, but also measured, will be called "measurable characteristics". An important circumstance, which ends any branch of the tree, we will call "final". By analogy, we will use the concepts of the final subgoal, the final measurable characteristic.

As already noted, first, on the basis of a logical analysis of the purpose of the operation, the decision maker builds a “tree of goals”. This is the first stage. In this case, the goal tree should be built either on the basis of a detailed description of the “desired” state (chain), or the decomposition of the “actual” state (which does not satisfy the decision maker in it, which must be eliminated). In fact, this is the same thing, because the decision maker must understand "what it wants." However, in terms of the form of logical activity, these are different approaches (like synthesis and analysis).

If the goal tree is built on the basis of the analysis of the "desired" state, it is more convenient to display the branching procedure graphically. The result of building a goal tree is not unambiguous. This is due to the fact that each decision maker decides for himself when to end the branching of goals. At the second stage, in the constructed tree of goals, each of the final particular tasks is associated with a method known from practice for solving it. The result is a decision tree. But since the goal tree is a subjective product of the creative activity of the decision maker, then the decision tree will most likely turn out to be unique, since the decision maker determines which heuristic methods to adopt for solving certain final tasks.

If the decomposition process is carried out during the analysis of the essence of the "real" state, then in this case the decision maker seeks to identify those "important circumstances" that, according to the decision maker, must be changed to achieve the goal. These important circumstances are also depicted in the form of a tree. After that, the decision maker again has only to replace all the important final circumstances in the resulting tree with specific heuristic ways to change them and get a decision tree. A feature of the technology for constructing a decision tree by decomposition of the "actual state" is that each of the important circumstances could be described by a measurable characteristic. If such a requirement is met, then it can be argued that the representation of the "actual state" will be unambiguous. In practice, the degree of unambiguous perception is determined by the degree of perfection of the scales used to describe the final elements.

Finally, it should be borne in mind that all the options obtained by the decision tree method can be mutually exclusive or compatible. If the options are mutually exclusive, then the number of possible alternatives is equal to the number of branches in the tree. For the case of compatible solutions, the number of alternatives is determined by the number of admissible combinations of solutions. The advantage of the decision tree method is the visibility and logical completeness of the set of alternatives. The disadvantage of this procedure is its cumbersomeness (however, all graphic-analytical methods sin with this).

The method of morphological tables, on the one hand, is a certain modification of the decision tree method. On the other hand, at a certain stage of the work, the decision maker abstracts from the essence of the final heuristic methods or techniques in order to generate non-traditional (previously unknown) options. To do this, the decomposition method is actively used for the informal and abstract (formal) stages of the process of the method.

First (informal, heuristic stage), the known methods of solving the problem are written out in an arbitrary order. Then these methods are analyzed (formal, logical stage) in order to identify their common system properties.

Acting in this way, it is possible to distinguish classes of methods of action and objects of application of efforts. The names of these classes are further used as headings of the morphological table (names of rows and columns). To facilitate the construction of a morphological table, the following sequence of actions is usually followed:

§ add to the morphological table ways to solve the problem from the compiled list;

§ consider sequentially each empty cell of the table. At the same time, based on your personal experience, intuition, or with the help of experts, formulate at least one simple solution for the considered combination of the object of application of efforts and the method of action.

Among the abstract-logical (mathematical) methods of generating alternatives, we include those that allow you to abstract from the essence of specific actions or methods of work, focus only on their sequence. To do this, you usually have to first build a mathematical model for the entire operation. Typical representatives of such methods for forming the initial set of alternatives are methods for forming plans for the execution of interrelated work (network planning and management methods) and scheduling methods.

Reflexive methods for generating alternatives are used when the leading type of uncertainty is behavioral. The method is based on the sequential hypotheses about possible purposes another subject of the operation and the formation of responses on the assumption that he will not change his line of behavior under any circumstances. Form a list of possible alternatives to decision makers. Once this is done, a "parallel list" of the opponent's responses is started. The resulting list of responses is then analyzed to find weaknesses and possible counter-actions of the subject of the operation on any action of the operating party. Thus, the "parallel lists" of alternatives of subjects are corrected and refined one by one. The reflexive action-counteraction process is repeated until the sets of actions and reactions stabilize.

A special class is formed by the methods of forming alternatives for the case when the decision is developed by a "group decision maker". In such a collective governing body, one can always see both full and partial coincidence of interests of the participants in the decision-making process, and various kinds of conflicts of interest. Often, discrepancies of interests are explained by an unequal interpretation of the goals of actions, due to the individual characteristics of the perception of a problem situation. Sometimes this may be the result of deliberate actions of individual sovereign participants in the “collective decision maker”. A typical example is departmental interests or a purposeful destructive policy. This is very characteristic of economic, social and political conflicts. It is in such situations that reflexive methods are most effective.

Achieving a certain goal or, more precisely, moving towards a certain goal implies choosing an alternative from a set of alternatives. A criterion or a system of criteria will allow you to choose exactly the right alternative from the set. The theory of choice takes a somewhat formal approach to the problem of creating a set of alternatives and assumes that the set of alternatives is given, i.e. there is something to choose from. The main question is how to choose. This approach – a clear example of a purely formal problem statement: all the main, fundamental difficulties are considered to have already been overcome, and we are talking, one might say, about technical difficulties. But it is precisely the formation of a multitude of alternatives that is the most difficult, most creative stage of system analysis. So, according to A. Hall, the stage of searching for ideas is the culmination point of the process of solving a problem, because without ideas there is nothing to analyze and choose.

How to choose is a purely technical process, but specifying a set of alternatives is the most creative, responsible stage of system analysis. The fact is that all our efforts are aimed at finding the best alternative in a given set. And if the best alternative is not included in this set for some reason, then no selection methods will calculate it. From the point of view of mathematics, the set of alternatives can be interpreted as the vertices of the simplex, and the best alternative as the vertex of the simplex that maximizes the objective function.

There are various ways to generate alternatives:

1) attraction of qualified experts with diverse training and experience - brainstorm;

2) generating alternatives through associative thinking, searching for analogies to the task ( synectics);

3) development of scenarios;

4) business game.

As a rule, when generating alternatives, specialists use the following simple rules: increasing the number of alternatives by combining them, creating favorable conditions for generating alternatives; reduction in the number of alternatives.

It is important to consciously generate as many alternatives as possible. Various methods are used for this. – search for alternatives in patent and journal literature; the involvement of several qualified experts with a variety of training and experience; an increase in the number of alternatives due to their combination, the formation of intermediate options between those proposed earlier; modification of an existing alternative, i.e. the formation of alternatives that are only partially different from the known; the inclusion of alternatives that are opposite to those proposed, including the “zero” alternative (“do nothing”, that is, consider the consequences of the development of events without our intervention); stakeholder interviews and broader questionnaires; including even those alternatives that at first glance seem primitive or far-fetched; generation of alternatives calculated for different time intervals (long-term, short-term, emergency); etc.

When organizing work at the stage of generating alternatives, it should be remembered that there are factors that inhibit creative work and those that contribute to it. Allocate internal (psychological) and external factors.

Internal factors include:

– consequences of misperception of reality; extreme manifestations – either we perceive what is not, or we do not perceive what is;

– intellectual barriers (inertia of thinking, prevailing stereotypes, subconscious self-restraints associated with beliefs, loyalty, etc.);

– emotional barriers, such as being too preoccupied with criticizing others or, conversely, fear of criticism from others, fear of a negative reaction from the customer or superiors to the proposed alternatives, subjective attitude towards the preferred types of alternatives (for example, some ardent supporters of the queuing theory try to reduced to priority tasks), etc.

TO external factors include:

– physical (weather and climatic) conditions that affect the productivity of creative work. Some researchers believe that there is a connection between the creative activity of entire peoples and the geographical conditions of their life. On individual activities physical conditions also play a role. It is said that Niels Bohr dismissed students from classes if it was so hot that the wax in the test tube melted; that Timofeev-Resovsky once, on a hot day, held a meeting of an international symposium right in the pond, and this was, according to the recollections of the participants, the most fruitful meeting. It is also known the negative impact of extraneous noise, various inconveniences on labor productivity;

– social conditions, general cultural background, ideological atmosphere, which have a significant impact on individual creativity; approval of a certain social group – one of the strongest stimuli for human creativity.

If we strive to ensure that as many alternatives as possible are obtained at the initial stage, then for some problems their number can reach many tens. Obviously, a detailed study of each of them will lead to unacceptable costs of time and money. In such cases, it is recommended to carry out a rough screening, not comparing the alternatives quantitatively, but only checking them for the presence of some qualities that are desirable for any acceptable alternative. Signs of good alternatives include stability under changing certain external conditions, reliability, multi-purpose suitability, adaptability, other features of practicality . The detection of negative side effects, failure to achieve control levels for some important indicators(for example, too high a cost), etc. Preliminary screening is not recommended to be carried out too harshly, at least several alternatives are needed for a detailed analysis.

Method brainstorming specially designed to get the maximum number of offers. Its effectiveness is amazing: six people can come up with 150 ideas in half an hour. A design team working by conventional methods would never have come to the conclusion that the problem under consideration has such a variety of aspects. This is the brainstorming technique. A group of individuals is assembled, selected to generate alternatives; main principle of selection – variety of professions, qualifications, experience (such a principle will help to expand the fund of a priori information that the group has). It is reported that any ideas that have arisen both individually and by association when listening to the proposals of other participants are welcome, including those that only partially improve other people's ideas (it is recommended to write each idea on a separate card). Any criticism is strictly prohibited this is the most important condition for brainstorming: the very possibility of criticism inhibits the imagination. Each in turn reads out his idea, the rest listen and write down on the cards new thoughts that arose under the influence of what they heard. Then all the cards are collected, sorted and analyzed, usually by another group of experts. The most remarkable thing is that the total result of the work of such a group, where the idea of ​​one can lead the other to something else, often exceeds the total number of ideas put forward by the same number of people, but working alone.

The number of alternatives can then be significantly increased by combining the generated ideas. Among the ideas obtained as a result of brainstorming, there may be many stupid and unworkable ideas, but such ideas are easily excluded by subsequent criticism, because competent criticism is easier to obtain than competent creativity. There are many examples of successful brainstorming. Here is just one of them, illustrating the usefulness of the prohibition of criticism. During the war, the problem of countering enemy mines and torpedoes at sea was brainstormed. One of the ideas was as follows: "Let, as soon as a mine or a torpedo is discovered, the whole team will stand on board and blow on it!". This seemingly frivolous idea was not rejected, and upon further analysis, the rational grain contained in it was transformed into a proposal to use powerful pumps to create water flows that repel a dangerous object.

Synectics is designed to generate alternatives through associative thinking, search for analogies to the task. In contrast to brainstorming, the goal here is not the number of alternatives, but the generation of a small number of alternatives (even a single alternative) that solve a given problem. The effectiveness of synectics has been demonstrated in solving specific technical problems such as “find a simple principle for the device of drives with a constant angular velocity”, “design an improved can opener”, “invent a stronger roof”, “develop a hermetic fastener for an astronaut's suit”. There is a known case of a synectic solution of more than common problem economic plan: "develop the new kind products with an annual sales potential of $300 million. There are attempts to use synectics in solving social problems such as "how to distribute public funds in the field of urban planning."

The essence of synectics can be summarized as follows. A group of 5 is formed – 7 people, selected on the basis of flexibility of thinking, practical experience(preference is given to people who have changed professions and specialties), psychological compatibility, sociability, mobility (the latter, as it will become clear from what follows, is very important). Once the group has developed certain skills in working together, the group engages in a systematic directed discussion of any analogies to the problem to be solved that spontaneously arise in the course of the conversations.

Synectics attaches particular importance to analogies generated by motor sensations. This is due to the fact that our natural motor reflexes are themselves highly organized and their understanding can suggest a good systemic idea. It is suggested, for example, to imagine one's body in the place of the mechanism being improved, to "feel like it", or to put oneself in the place of a fantastic organism that performs the function of the system being designed, etc. The emancipation of the imagination, intense creative work create an atmosphere of spiritual uplift, characteristic of synectics. There are also psychological difficulties that beginners experience when using this method: the appearance of remorse ("we get money for a pleasant pastime"); arrogance after the successful solution of the first problem; exhaustion of the nervous system as a result of intensive work.

The success of the work of synectic groups is facilitated by the observance of certain rules, in particular, it is forbidden to discuss the merits and demerits of members of the group; everyone has the right to stop work without any explanation at the slightest sign of fatigue; the role of leader periodically passes to other members of the group, etc.

In the United States, a special firm, Synectics, Incorporated, has been established to provide consulting and training in the field of synectics. We emphasize that, unlike brainstorming, when using synectics, special and lengthy preparation is required. During the year 5 or 6 people. must spend 1/4 of their working time on training. A team of trained full-time synectors is able to find acceptable solutions to about four minor and two major problems over the course of a year.

Scenario development. In some problems (especially in sociotechnical ones), the solution sought must determine the real future course of events. In such cases, alternatives are various (imaginary, but plausible) sequences of actions and events arising from them that may occur in the future with the system under study. These sequences have a common beginning (the present state), but then the possible states differ more and more, which leads to the problem of choice. Such hypothetical alternative descriptions what might happen in the future is called scripts, and the method in question – scenario development. Alternative scenarios are of value to decision makers only when they are not just a fantasy, but logical models of the future, which, after the decision is made, can be considered as a prediction, as an acceptable story about what will happen if ...

Scripting refers to typical non-formalizable procedures, is a creative, scientific work. Nevertheless, certain experience has been accumulated in this matter, and there are some heuristics. For example, it is recommended to develop "upper" (optimistic) and "lower" (pessimistic) scenarios – as if extreme cases, between which there may be a possible future. This technique allows one to partly compensate or explicitly express the uncertainties associated with predicting the future. Sometimes it is useful to include an imaginary actively opposing element in the scenario, thus modeling the "worst case". In addition, it is recommended not to develop detailed (as unreliable and impractical) scenarios that are too “sensitive” to small deviations in the early stages.

Important steps in creating scenarios include: compiling a list of factors influencing the course of events, with a special allocation of persons who control these factors directly or indirectly; highlighting aspects of the fight against such factors as incompetence, negligence and indiscipline, bureaucracy and red tape; accounting for available resources, etc.

Morphological analysis - simple and effective method generating alternatives. It consists in selecting all independent variables of the designed system, listing the possible values ​​of these variables and generating alternatives by enumeration of all possible combinations of these values.

Let us illustrate the essence of morphological analysis on a simplified example of the development of a television communication system (Table 1)

Table 1

Tab. 1 generates 8 · 2 · 2 · 3 · 2 · 2 = 384 different possible systems. Only one alternative corresponds to modern television broadcasting: 1.4 – 2.1 – 3.1 – 4.2 – 5.1 – 6.1. There is reason to wonder why other alternatives have not yet attracted the attention of engineers.

We also note that the number of options can be increased by introducing new independent variables (in the example considered, enter image sizes with gradation from today's usual to the size of the entire wall, introduce additional information transmission channels, for example, skin-electric or tactile; switch from a single-screen system to multi-screen, etc.). One of the main problems of morphological analysis with an increase in the number of variables – it's a bust reduction problem. It is solved by imposing various restrictions that allow us to discard options that are not subject to consideration.

business game called simulation of real situations, during which the participants in the game behave as if they actually perform the role assigned to them, and reality itself is replaced by some model. Examples are staff games and maneuvers of the military, work on simulators of various operators of technical systems (pilots, power plant dispatchers, etc.), administrative games, etc. Despite the fact that most often business games are used for learning, they can also be used to experimentally generate alternatives, especially in poorly formalized situations. An important role in business games, in addition to the participants, is played by control and arbitration groups that manage the model, register the course of the game and summarize its results.

The main purpose of the decision maker and its final product management activities is the development of solutions. Of course, other important managerial functions, such as the organization of interaction, comprehensive support for the conduct of the operation, control, assistance, assessment of the actual effectiveness of the operation, fixation, generalization and dissemination of the experience gained during the operation.

Acceptance Structure Diagram management decisions presented in Fig.1.7.

The basis for making all decisions at all stages of the decision-making process, of course, is the preferences of the decision maker.

Undoubtedly, the formalization of preferences should be the appropriate beginning of the decision-making process.

After the preferences of the decision maker are formalized and the necessary information about the preferences is obtained, they proceed to the next important decision-making step - to the construction of the choice (utility) function.

The choice function in decision theory has fundamental. It is precisely on its construction that the solution of the problems of forming the initial set of alternatives, analyzing the conditions for conducting the operation, identifying and measuring the preferences of the decision maker are ultimately oriented.

According to the formal definition adopted in the TPR, the choice function is a mapping of the form

where is a set (initial for the considered decision-making step), from which a choice is made; - a subset that has certain (known or given) properties, and

When obtaining information about preferences from the decision maker step by step in the course of measurements, a selection function is first constructed based on the results of measurement and evaluation in the most reliable, but also less accurate nominal scale, based on qualitative judgments about preferences. As a result, from the initial set A of alternatives, the first representation of the desired subset of alternatives is obtained, which contains the best alternative.

If the decision maker, having conducted an informal analysis of the subset, has not yet been able to decide on the choice, then the construction of the choice function should be continued. To do this, the decision maker must clarify the measured preferences by using a more advanced, for example, ordinal or point scale, to measure them.

As a result of refining the form of the choice function, in the general case, a different subset of alternatives will be obtained, moreover. Now the decision maker must focus on the analysis of this last set, since again the best alternative is contained in it. Then, if necessary, the decision maker's preferences can be clarified again by measuring them in any of the proportional scales, and so on until the decision maker confidently stops in choosing the best alternative.

It should be borne in mind that the specific form of the choice function that implements mapping (1.3) depends on the mechanism of the situation.

This circumstance is noted in the diagram Fig.1.7. options for constructing a choice function with their detailing according to the type of uncertainty conditions: under conditions of stochastic uncertainty, under conditions of behavioral uncertainty and under conditions of natural uncertainty.

The target difference in the use of scalar and vector criteria determined the need to display in Fig. 1.7 in the general case two options for the form of initial data and procedures for constructing a selection function - according to a scalar or vector criterion.

Receiving the information

The decision-making process requires the fullest possible amount of information both about the control system itself and about the environment of its operation ( environment). Without information of this kind, it is impossible to analyze the conditions for making decisions, identify the mechanism of the situation, and form the initial set of alternatives. The decision maker must carry out a meaningful analysis of information about the conditions of the operation, and obtain reliable ideas about the mechanism of the situation. Only by acquiring this information, the decision maker will be able, from the standpoint of systems approach not only verbally describe the main (leading) factors that contribute to and hinder the formation of a successful outcome of the operation, but also formally assess the degree of their influence on the effectiveness of the outcome.

To do this, it is necessary to understand exactly what information, of what quality and by what date is needed. The result of this intermediate decision (content, the required accuracy and reliability of information, the speed of its receipt) will help the decision maker to consciously choose one of the available sources of information and make a decision. The classification scheme of possible sources and ways of obtaining information is shown in Fig. 1.8.

From the analysis of the circuit in Fig. 1.8. It follows that in principle there are only three sources of information:

Empirical data

· knowledge, personal experience and intuition of the decision maker;

expert advice (expertise).

It is clear that almost most often people draw information from their own experience and knowledge, and their own intuition helps them fill in the gaps in positive knowledge.

In addition, there are two more fundamental possibilities: to search for the necessary information in one of the "objective sources", where the historical experience of mankind (empirical data) is recorded, or to turn to a "subjective source" - to the knowledge, skills and abilities of recognized specialists in their field (experts) .

The TPR believes that an expert is a person who personally works in the field of activity under consideration, is a recognized specialist in the problem being solved, and can and has the opportunity to express an opinion on it in a form accessible to the decision maker.

Experts perform informational and analytical work based on their personal ideas about the problem being solved. In the general case, the views of experts may not coincide with the opinion of the decision maker. This difference of opinion plays both negative and positive role. On the one hand, when opinions differ, the process of developing a decision is delayed, but, on the other hand, the decision maker can critically comprehend an alternative point of view or correct his own preferences.

In order to increase personal confidence that the specialist gave him the right advice, the decision maker may turn to not one, but several experts. Accordingly, there are individual (one expert) and group expertise. If the question is strictly confidential, time is limited or there is no opportunity to ask several specialists for an answer to a question of interest, then an individual examination is the best way to obtain information. But if the listed restrictions are not significant, then, undoubtedly, group examination is, on the whole, a more reliable and accurate way of obtaining information.

At the same time, in the course of a group examination, a discrepancy between the subjective judgments of individual specialists is possible. In this regard, it is required to take special methods of processing expert information in order to increase the reliability of the results.

TPR has developed a special set of organizational, technical and mathematical procedures that give harmony and logical conditionality to the entire process of obtaining, processing and analyzing group expert information. This set of procedures, which includes expertise (that is, the survey of experts itself) as only one of the stages of obtaining information, is called the method of expert evaluation in the TPR.

Historically accumulating knowledge, having learned to write, people began to record their objective experience. All useful information began to be entered in one form or another on special media. At first, these media were imperfect (for example, manuscripts, books) and inaccessible, but gradually they acquired a more perfect form, and with the development of printing, they turned into libraries, data banks (BnD), databases (BzD) and knowledge bases (BzZ) . The process of searching for publicly available information has become more convenient, efficient and even creative. But at the same time, some information and some sources of information became inaccessible to the general public. Therefore, in the case when the decision maker, for various reasons, cannot find the information he needs in public sources, it has to be actively extracted. In order to obtain inaccessible information, the decision maker can organize and conduct a full-scale or model experiment, he can resort to the help of intelligence or use some kind of special equipment.

Intelligence or special equipment require significant costs; the same applies to the experiment, especially if the experiment is large-scale and is carried out under the action of an ambiguous mechanism of the situation. Therefore, in order to save money, it is advisable to carry out strictly scientific planning experiment, quantitatively establish its parameters that are optimal in terms of the effectiveness of future decisions and actions of the decision maker.

Significant theoretical progress has been made in planning experiments on mathematical models using computers. The apparatus of the mathematical theory of planning is mainly focused on the study of random mechanisms of the situation. At the same time, it is often useful in other situations.

Let us consider the statement of the experiment planning problem.

If the goal of the study is to maximize the beneficial effect of the experiment under cost constraints, and the beneficial effect itself is correlated in the mind of the decision maker with providing an extremum (for example, maximum) of the output result, then the problem of establishing the optimal parameters of the experiment will be reduced to the desire to maximize the output result under cost constraints. For example, if you need to increase the yield of some useful substance in the process of chemical production, and the yield depends on such important parameters as temperature, pressure, etc., then the problem statement for planning an experiment for the production of a chemical product may look like this: find the optimal combination listed controlled variables of the chemical production process, which provide the maximum yield of the finished product of the required quality, provided that the cost of the experiment is not higher than the finances allocated for it.

Approximately according to the same scheme, the statement of the problem for obtaining information is formulated in the case when the effect is identified with the accuracy of predicting the output result, that is, with the magnitude of the error in reproducing the mechanism of the situation, as well as the statement of the problem, in which the goal of the decision maker is to strive to minimize the costs of modeling while ensuring the levels of claims of the decision maker for the expected effect.

The problem of forming the initial set of alternatives

This problem has already been mentioned in the previous lecture. Given its exceptional importance, let's consider it in more detail.

The degree of experience of the decision maker is largely characterized by the ability to correctly predict the situation and find the best way to solve the problem. At the same time, to correctly determine the mechanism of the situation means to quickly establish the leading factors, and the ability of the decision maker to generate new, non-standard solutions is generally identified in the minds of people with art. In this regard, it is clear that the task of forming the initial set of alternatives cannot be fully formalized. Solving this problem is a creative process, in which the main role, of course, belongs to the decision maker. The emergence of this problem as a theoretical object of study is a direct consequence of the use of the system principle of the plurality of alternatives in the TPR.

Before solving the problem of forming the initial set of alternatives, it is necessary to determine the system requirements that this set must meet. First, the set of alternatives should be as complete as possible. In the future, this will provide the necessary freedom of choice for decision makers and will minimize the possibility of missing out on the “best” solution. However, this first fundamental requirement is in conflict with the second, arising from the principle of matching the solution to the time, place and capabilities of the decision maker. Most often, in practice, such compliance is understood as a requirement to develop a solution as soon as possible. Therefore, secondly, the initial set of alternatives should be visible, narrow enough so that the decision maker has enough time to assess the consequences and preference of alternatives under the existing resource constraints. The problem of meeting these two conflicting requirements is solved systematically, based on the principle of decomposition.

Following the systemic principle of decomposition, at first a set of alternatives is formed, all elements of which potentially, according to their appearance, according to the possibilities hidden in them, ensure the achievement of the target result in the current situation. The set of applicants for the method of solving the problem obtained in this way will be called the set of target alternatives.

Then, from the set of target alternatives, those options are selected that are logically consistent and can be implemented within the time allotted for the operation. In addition, the selected alternatives must be satisfied with the necessary active resources and must comply with the general preference system of the decision maker.

We will call these options selected from the target alternatives physically realizable alternatives from among the target ones. The remaining options, potentially leading to the goal, but physically unrealizable, are discarded.

The options obtained as a result of such manipulations are complemented by methods of action that give the alternatives the necessary flexibility and stability in relation to the changing or currently unknown components of the operation conditions. As a result, they get the original set of alternatives.

Technologically, the method of forming the initial set of alternatives involves a number of special purposeful modifications of the main factors of the situation mechanism. They consist in the simultaneous or sequential impact on the controlled (subject to the will of the decision maker) part of the characteristics of the quality of the active resources used, the characteristics of the conditions and methods of action.

It is this idea that underlies most of the known methods and algorithms for the formation of the initial set of alternatives.

Historically, the first to appear are empirical methods that require minimal formalization. The simplest of this class is the method based on the use of a cause-and-effect diagram. A typical modern representative of empirical methods is the CBR method (Case-Based Reasoning - "method of reasoning based on past experience").

The next class is formed by logical-heuristic procedures, where formalization is carried out at the level of managing logical relationships. As examples of the implementation of such methods are the decision tree methods and the method of morphological tables.

Typical representatives of the class of methods for generating alternatives, in which the greatest degree of formalization of all stages of generation has been achieved, are the methods of network and scheduling.

A special class is formed by the methods of forming alternatives in conditions where the decision is developed by a "group decision maker", when there is a complete or partial coincidence of interests of the participants in the decision-making process, however, due to the unequal interpretation of the goals of actions, the peculiarities of the individual perception of the problem situation, and for other reasons, the sovereign opinions of the participants the decision-making process must be agreed upon in the overall decision. Other representatives of the methods of this class are the methods of generating alternatives in the conditions of conflict and opposition of sovereign subjects involved in the operation of decision makers either of their own free will or against their will. Such situations are characteristic of economic, social, political and military conflicts. In all such situations, as a rule, reflexive methods are used to form alternatives. Such methods are characterized by an average level of formalization using simple mathematical models.

In terms of frequency of application in practice, perhaps the first place is occupied by logical-heuristic methods. They acquired this position due to their inherent visibility, simplicity and universality of the approach, the convenience of computerization of their algorithms. The essence of these methods is that at first, on the basis of a logical analysis of the purpose of the operation, a tree of goals and objectives is built. Then each subgoal or task is also detailed, and this operation continues until the decision maker becomes clear which of the known means (or in what way) to solve each particular task.

Evaluation of alternatives

As already noted, a conscious choice should be made on the basis of a comparison of the results of the evaluation of alternatives. Therefore, the task of evaluating alternatives has the main goal of obtaining for each alternative the values ​​of the results that characterize the intensity of the essential properties of the outcomes of the operation planned to be carried out under given conditions. Let us formulate the task of evaluating alternatives as the task of obtaining results for each alternative, as follows.

A set A of decision maker alternatives that characterize the procedure for using available resources to achieve the goal of the operation; a set of S factors that set the conditions for the operation to achieve the goal, and their quantitative and qualitative characteristics; type of situation mechanism.

Required

Estimate the value of the result Y(a, s) for each of the alternatives of the set A under conditions S.

Depending on the type of the mechanism of the situation, the result Y(а, s) of applying the alternative, and under the conditions s, will be understood differently.

If the mechanism is deterministic, then the result Y(a) (generally vector) depends uniquely on the alternative, the conditions are fixed and determine only the form of the mapping A --> Y.

For the stochastic mechanism of the situation, in the general case, each alternative is assigned a probabilistic distribution of the vector result, the conditions are fixed and determine the type of probability distribution. For other types of the situation mechanism, we will look for the set of possible values ​​of the vector result Y(а, s).

Information about the values ​​(estimates) of the result Y(a, s) for any of the listed types of situation mechanisms can be obtained in various ways, but the main means of obtaining new information to solve large-scale problems should be considered mathematical modeling.

Modeling should be organized as a process of building models with a gradually increasing "image scale". At the same time, at the initial stage of the modeling process, models of the highest degree of generalization of factors are used, taking into account only the most noticeable patterns - the so-called conceptual models (this is the "smallest scale" of the study). Then the object of study is refined and the model is supplemented by introducing a larger number of factors into it and measuring their characteristics on scales of an intermediate degree of perfection ("medium scale"). Finally, when the researcher is so determined in the object of study that he singled out a specific element from reality and decided which patterns to reproduce in all details, they carry out detailed modeling (the "largest scale" of the study) using the most advanced, quantitative scales.

The experience of decision-making based on simulation shows that in any case, the results obtained during the simulation will contribute to a deeper understanding of the essence of the operation and improve existing methods managing it.

An important independent element of the model development process is to check its performance.

Among such checks, many researchers first of all usually name checks for consistency with common sense (simulation results are consistent with ordinary ideas), asymptotic stability (limiting minimum or maximum values ​​of input parameters lead to correct conclusions, confirmed by asymptotic estimates), sensitivity to important parameters(the model responds to small changes in the input parameters), compliance with experimental data (the results of the experiment should be well reproduced on the model), efficiency (the ability to obtain the results required in terms of quality within the allotted directive timeframes).

After establishing the adequacy of the model, they proceed to obtaining and processing the simulation results necessary for making a decision. Data processing is carried out in order to make them visible and bring them to a form convenient for decision making. The method of data processing is chosen depending on the type of scale (qualitative or quantitative) and the nature of the factor corresponding to these data (random, "natural", etc.).

The results of experimental data processing must be presented to decision makers in a concise and expressive form, with the required degree of detail.

If you ask a person who is well versed in management problems how he could characterize the degree of experience of a manager, then most often you can find the following answer: the ability to predict the situation and quickly find the best way to solve the problem. But what is the “best way to solve?” how to form ways to achieve the goal of the operation in general?

before offering best approach To solve the problem, it is necessary to determine the system requirements that the set of alternatives must meet.

First, the set of alternatives should be as wide as possible. But this requirement is in conflict with the natural restrictions on time, place and opportunities in which the decision maker usually has to work. It is impossible to develop a solution indefinitely. Otherwise, there will not be enough time to implement it. This implies the second requirement of the set of alternatives - it should be visible, narrow enough so that the decision maker has more time to evaluate the preference of alternatives, and the performers have more time to implement the found best solution in practice.

In cases of deterministic or naturally indeterminate mechanisms of the situation, the method of forming the initial set of alternatives involves the improvement of fairly simple actions. At the same time, the decision maker explores the possibility of simultaneously influencing the "controlled" component of these factors, since it is precisely this method of control that most often leads to the emergence of positive properties in future alternatives. Moreover, if the decision maker intentionally affects, for example, the quality of active resources, then in this case all methods of forming alternatives are classified as so-called engineering synthesis. If the objects of the application of the efforts of the decision maker will be factors from the classes "Conditions" and "Methods", then we will have in mind the methods operational synthesis solution options. The set of options for solving the problem obtained in the course of engineering or operational synthesis will be called the set target alternatives. After receiving the target alternatives from the set, it is necessary to select those options that are logically consistent and can be implemented within the time allotted for the operation. Let's call these options physically realizable.

The obtained subset of physically realizable alternatives is supplemented with options that provide the necessary flexibility and stability in relation to possible changes in future conditions of operations. As a result of the work done, they get what we will later call original set of alternatives.

Conventionally, all methods of forming a set of alternatives can be divided into classes that differ in the degree of formalization of the technologies used:

empirical

logical-heuristic

abstract-logical

reflexive.

First arose empirical method. Meaning - common feature inherent in certain practical methods for solving specific problems. Logical-heuristic- involve the gradual division of the problem or task under consideration into separate subtasks, questions, to such elementary actions for which heuristic solutions and specific technologies for their implementation are already known. Among the abstract-logical methods of generating alternatives, we will refer to those that allow you to abstract from the essence of specific actions or methods of work, focus only on their sequence. Typical representatives of such methods of forming the initial set of alternatives are the methods of forming plans for the execution of interrelated work and scheduling methods. reflexive used when the leading type of uncertainty is behavioral. The method is based on the consistent hypotheses about the possible goals of another subject of operations and the formation of responses on the assumption that he will not change his line of behavior under any circumstances. Form a list of possible alternatives to decision makers. Once this is done, a "parallel list" of the opponent's responses is started. The generated list of responses is then analyzed in order to find weaknesses and possible counter-actions of the subject of the operation to any action of the operating side. Thus, the "parallel lists" of alternatives of subjects are corrected and refined one by one.