Interval-valued fuzzy multiple criteria decision-making methods based on dual optimistic/pessimistic estimations in averaging operations

Abstract

This study aimed to consider the effect of dispositional optimism and pessimism to provide simple and useful decision models and methods for multiple criteria decision analysis within an interval-valued fuzzy environment. Uncertain and imprecise assessment information is usually present in many practical decision-making situations. Interval-valued fuzzy sets are useful for modeling impressions and quantifying the ambiguous nature of subjective judgments in a convenient way. Based on measurement tool estimations defined on interval-valued fuzzy sets, dual optimistic and pessimistic point operators were utilized in this study, and this paper discusses several important properties of optimistic/pessimistic averaging operations. Two algorithmic procedures were developed to address the effects of optimism and pessimism, involving changes in overall judgments and in the separate evaluations of alternatives with respect to each criterion. Furthermore, this study explored the practical problem of medical decision making to demonstrate the feasibility and applicability of the proposed method and to make a comparison with other existing methods. Finally, computational experiments were designed using enormous amounts of simulation data, and a comparative analysis of rank orders yielded by dual optimistic and pessimistic averaging operations was conducted.