EXPERT KNOWLEDGE ANALYSIS TECHNOLOGY WITH FUZZY PREFERENCE RELATION

Abstract

The adoption of managerial decisions occurring in complex social, economic, technical, organizational and other systems quite often occurs under a certain amount of conflicting factors that describe the most complex processes occurring in such systems. In this case, a decision-maker (expert) cannot guarantee an effective decision at the heuristic level, especially in a situation where it is difficult for an expert to express his/her preferences unambiguously, or the input data is not crisp, or is given with a certain degree of reliability, belonging to certain categories. To support the processes of preparation and synthesis of decisions under uncertainty (fuzziness), a well-developed apparatus of the fuzzy set theory and fuzzy relations is used, which makes it possible to correctly operate with various kinds of vague, fuzzy, uncertain concepts. The purpose of the paper is to consider one of the possible approaches to solving the problem of ordering multicriteria alternatives using fuzzy binary relations. The considered approach is based on the procedure for the synthesis of the resulting fuzzy binary relation as the intersection of the original fuzzy relations of a non-strict order. Based on the resulting fuzzy binary relation that satisfies the three conditions for the presence of a fuzzy order relation over it (the condition of reflexivity, antisymmetry and transitivity), the choice of the best alternative is made. Methodology of the study is based on general research methods of system analysis, the theory of decision-making, the theory of sets, the fuzzy set theory and fuzzy relations were used in the research process. The methods of the fuzzy set theory and fuzzy relations are used for fuzziness modeling; decision-making methods are applied when solving the problems of choosing the best alternative, ranking alternatives by significance. Results of the survey showed that the considered approach for multi-criteria problem solving, provided that the initial expert information is given in the form of fuzzy binary relations, becomes a theoretical basis for the synthesis of information technologies for intellectual resources (data and expert knowledge) managing with the aim of preparing information for making reasonable and effective decisions under incompleteness, uncertainty, and vagueness. Practical implicationsof the obtained results lie in the fact that the considered approach can be the basis of methods, algorithms and information technologies of intellectual decision-making support and its implementation as part of automated decision support systems in case when solving the task of ordering multi-criteria alternatives under inaccuracy, ambiguity and uncertainty. Value/originality. The proposed approach allows to model the uncertainty in expert judgments, through the presentation of inaccuracy (vagueness, fuzziness) in experts’ assessments in the form of fuzzy binary relations. The algorithm of this approach is easily implemented computationally and can be useful for solving a number of practical problems.