Multi-Criteria Group Decision-Making Using an m-Polar Hesitant Fuzzy TOPSIS Approach

Abstract

The m-polar fuzzy sets (mF sets) have a representative and fundamental role in several fields of science and decision-making. The fusion of mF sets with several other theories of mathematics has become a favorable practice for depicting numerous types of uncertainties under multi-polar information. In this article, we introduce an innovative hybrid model, called m-polar hesitant fuzzy sets (mHF-sets), a hybridization of hesitancy and mF sets, which enables us to tackle multi-polar information with hesitancy. Hesitancy incorporates symmetry into the treatment of the data, whereas the m-polar fuzzy format allows for differentiated or asymmetric sources of information. We highlight and explore basic key properties of mHF-sets and formulate intrinsic operations. Moreover, we develop an m-polar hesitant fuzzy TOPSIS (mHF-TOPSIS) approach for multi-criteria group decision-making (MCGDM), which is a natural extension of the TOPSIS method to this framework. We describe applications of mHF-sets in group decision-making. Further, we show the efficiency of our proposed approach by applying it to the industrial field. Finally, we generate a computer programming code that implements our decision-making procedure for ease of lengthy calculations.