Multi-Attribute Group Decision Making Based on Bipolar-Valued Fuzzy Multigranulation Rough Sets over Two Universes

Chao Zhang, Deyu Li

Abstract: As a significant multi-granularity computing model in the rough set community, multigranulation rough sets (MGRSs) establish multi-dimension and multi-view problem solving methods through providing synthesis and analysis strategies for solution space in different granularity levels, which act as a powerful tool for coping with various complicated multi-attribute group decision making (MAGDM) problems. The main point of interest in this work is to apply the concept of bipolar-valued fuzzy sets (BVFSs) to MGRSs. Firstly, the definition of bipolar-valued fuzzy multigranulation rough sets (BVF MGRSs) over two universes is presented. Then, we construct a MAGDM method on the basis of BVF MGRSs over two universes. Finally, a case study is provided to show the validation and practicality of the newly constructed method.