METHOD FOR PROCESSING SUBJECTIVE EXPERT INFORMATION FOR DECISION MAKING USING FUZZY SETS THEORY 

Vyacheslav V. Antonov, Doctor of technical sciences, professor, head of the sub-department of automated control systems, Ufa University of Science and Technology (12 K. Marksa street, Ufa, Russia), E-mail: Antonov.V@bashkortostan.ru
Konstantin A. Konev, Candidate of technical sciences, associate professor, associate professor of the sub-department of automated control systems, Ufa University of Science and Technology (12 K. Marksa street, Ufa, Russia), E-mail: sireo@rambler.ru 

Background. Decision making issues are key for any organization. The problem in the decision-making process is the high uncertainty regarding the results of decisions made due to the subjectivity of experts. To solve this urgent problem, the article aims to develop a method for processing subjective information from experts in the decision-making process in an organization through the use of fuzzy logic. Materials and methods. The research used scientific works of foreign and domestic scientists devoted to study in the field of decision making, fuzzy logic, category theory and data mining aimed at reducing the subjectivity of experts. Results. The article proposes a structure of decision-making elements in an organization for a decision support system, formulates expressions for the quantitative assessment of fuzzy sets for typical situations using evaluative categories built on the basis of expert assessments and develops an example for a typical situation of a procurement business process in an organization. Conclusions. There was developed and tested a method for processing subjective expert information using fuzzy logic, suitable for use in decision making at an industrial enterprise. 

decision making process, subjective expert information, fuzzy sets, category theory, expert assessments 

Antonov V.V., Konev K.A. Method for processing subjective expert information for decision making using fuzzy sets theory. Modeli, sistemy, seti v ekonomike, tekhnike, prirode i obshchestve = Models, systems, networks in economics, technology, nature and society. 2024;(1):65–78. (In Russ.). doi: 10.21685/2227-8486-2024-1-5