Models of information situations of decision-making under conditions of risk, uncertainty, and fuzzy information

The relevance is conditioned by the need to create mathematical support for a conceptual approach that would allow systematising information situations of decision-making under conditions of risk, uncertainty, fuzzy information, and provide a reasonable choice of methods for solving practical decision-making problems in these situations. The goal was to develop mathematical models of information situations of decision-making under conditions of risk, uncertainty, fuzzy information, and their possible combinations, and to build a model of the decision-making process based on them, which provides for the possibility of applying several methods of choosing alternatives and aggregating their results to improve the efficiency of decision-making. The research methodology was based on a systematic approach using set theory, probability theory, fuzzy set theory, decision theory and methods, and mathematical modelling to formalise information situations of decision-making. Mathematical models of information situations of decision-making under conditions of risk (Risk, R), complete uncertainty (Uncertainty, U), fuzzy information (Fuzzy, F), and possible combinations of situations were developed: R-U, R-F, U-F, R-U-F. The generalised model of information situation of decision-making R-U-F (MISDMRUF) was interpreted as a model of a decision-making problem that formalises the process of choosing an alternative in conditions of simultaneous presence of risk, uncertainty, and fuzzy information. This allowed using existing and creating new decision-making methods depending on the characteristics of the information situation of decisionmaking. A model of the decision-making process under conditions of risk, uncertainty and fuzzy information (MDMPRUF) was proposed, its tasks, main stages of implementation, and key features, in particular, versatility, flexibility, and integrativity, were defined. The results showed that the proposed MISDMRUF and MDMPRUF models were consistent with a number of studies in decision theory, but simultaneously fill in the existing gaps, providing a systematic, integrated approach to classifying information situations of decision-making and selecting decision methods under complex conditions of risk, uncertainty, and fuzzy information. The proposed mathematical models and an appropriate approach to solving decision-making problems can become the basis for creating information technologies for decision support under complex conditions