УДОСКОНАЛЕННЯ НАУКОВО-МЕТОДИЧНОГО АПАРАТУ РОЗКРИТТЯ НЕВИЗНАЧЕНОСТІ В ЗАДАЧАХ ВЗАЄМОДІЇ

Abstract

For a large class of systems analysis tasks, an important issue is the disclosure of uncertainties. This is due to the variety of goals, properties and characteristics of the studied objects. Today, the task of revealing the uncertainty of conflicts in the tasks of choosing the goals of plans and plans in the process of interaction of partners or opposition of competitors or opponents remains relevant. There are methods in systems analysis that allow you to solve these problems in some cases. They are based on the application of methods of mathematical analysis and probability theory. However, these methods are applicable only to problems in which the number of partners and the arguments of the objective functions that determine the purpose of their activities coincide. Since in practice, as a rule, such a restriction is not met, it is important to find approaches to solving problems of disclosing the uncertainty of conflicts in the tasks of choosing the goals of plans and plans in the process of interaction of partners arbitrary number of partners and arguments of their target functions. The paper formalizes the problem of revealing uncertainty in the interaction of partners, in which the number of arguments of the objective functions is not necessarily equal to the number of partners. The analysis of the existing approach to the solution of the formulated problem in the absence and presence of situational uncertainty for two and any number of partners is also carried out. Based on the application of technical constraints, an approach to solving the problem is proposed and software and algorithmic support for its implementation is formed. This approach is based on the preliminary formation of the area of acceptable solutions (Pareto area) and the subsequent search for a rational solution in this area. The proposed approach can be applied to solving the problem of disclosing the uncertainty of conflicts both in the absence and in the presence of situational uncertainty. Software-algorithmic implementation of the author's approach to solving the research problem allows to automate individual stages of problem solving.