Study of Decision-Making Models Based on Z-Numbers while Solving Problems with Incomplete Information

Abstract

In this article, the decision-making models based on Z-numbers were studied during the decision-making process under the conditions of incomplete information, and a number of scientific and practical issues related to their application in solving the given problem were reviewed. As a result of the research, it became clear that it is not easy to form a rational decision-making ability and make optimal decisions in conditions of uncertain, fuzzy or incomplete information based on existing approaches, and sometimes it is inaccurate. Thus, solving real decision-making problems, decision analysis, and systematic analysis in economics, ecology, and other fields are characterized by vagueness and partial reliability of certain data. In this regard, the Z-numbers proposed by Professor Zade have a strong effect in expressing the uncertainty due to the unique structure. This paper proposes a fuzzy approach for decision making based on Z-information based on the exact computation of Z-numbers in solving decision-making problems under the conditions of incomplete information. The approach is intended for hierarchical imprecise models. In the article, the models considered in relation to the research and application of decisionmaking models based on Z-numbers are based on the processing of uncertain information and the use of word computing technology in decision-making.