A study on Three-way decision methods based on uncertain and irresolute information

Abstract

Three-way decision (TWD) theory is based on human cognition and plays a vital role in everyday multi-criteria decision-making (MCDM) problems based on uncertain and irresolute information. Conflict, being an instinctive feature of human civilizations, exists in diverse real-life problems. Three-way decisions are more advantageous to resolve conflict problems, and its structure correlates with conflict analysis naturally. The current study mainly aims to improve TWD analysis to address the complex issues more significantly. For this, we propose a three-way conflict study analysis from a trade-off view point by incorporating game theory with rough set data analysis approach. Further, we present a three-way conflict analysis model to deal with hesitant fuzzy information system (HFIS). To exemplify the viability of proposed techniques, we resolve some real-life problems including the Syrian conflict, Middle East conflict, and the development problem of Gansu province China. Besides, detailed result analysis and comparative study are also provided. Another novel contribution of this thesis is to define some generalized operation rules for T-spherical fuzzy numbers (T-SFNs) by using Frank t-norm and Frank t-conorm, which can make more provision of options for the decision-makers. Additionally, we originate some T-spherical fuzzy frank aggregation operators and investigate some basic characteristics of these operators. By proposing the entropy measure for T-spherical fuzzy information, we generate a possibility to obtain the unknown weights information of the criteria. Then it is further used for criteria weight determination in the proposed aggregation based MCDM and TWD models. To validate the potentiality of the suggested approaches, we consider two practical cases concerning the investment problem. Moreover, in-depth comparative study and sensitivity analysis are also delineated.