BWM and MULTIMOORA-based multigranulation sequential three-way decision model for multi-attribute group decision-making problem

Abstract

This paper proposes a sequential three-way decision-making approach based on BWM (best-worst method) and MULTIMOORA for multiple levels of granularity to deal with the multi-attribute group decision-making problems under uncertainty. First, using BWM to preprocess the attribute indicators of the decision problem, the relationship between the criteria important for decision problem is determined. Then, according to the importance of the determined level of granularity, from rough to clear, three-way decisions are made in sequence at each level. In this way, we obtain a lattice based three-way decision-making process. Also, in the process at each granularity, we consider the costs of both the decision process and the decision result. Thus, this paper builds a multigranulation sequential three-way decisions model with cost-sensitive. Next, based on the above-mentioned model, we propose a decision procedure and an algorithm for multi-attribute group decision making. It is worth noting that according to the research goals of the decision problem, MULTIMOORA is used to sort the classified alternatives. And a ranking result of the decision problem is given. Finally, the effectiveness and validity of the proposed model is verified by a multi-attribute group decision problem. The problem is the case of emergency diagnosis and treatment after a highway accident. And put forward reasonable suggestions for further development direction.