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.
Highlights
Most of the classical tools for conventional modeling, computing, and reasoning are absolute, deterministic, and classic in character
Chen et al [21] generalized the concept of HFSs by proposing the idea of interval-valued hesitant fuzzy sets (IVHFSs)
In order to handle this kind of decision-making problems, in this article, we introduce the concept of mHF-sets with an associated novel approach of TOPSIS for multi-criteria group decision-making (MCGDM) problems
Summary
Most of the classical tools for conventional modeling, computing, and reasoning are absolute, deterministic, and classic in character. Alcantud and Torra [19] discussed extension principles and decomposition theorems for HFSs. On information fusion in decision-making, Rodríguez et al [20] provided a perspective analysis and position of HFSs. Chen et al [21] generalized the concept of HFSs by proposing the idea of interval-valued hesitant fuzzy sets (IVHFSs). Akram et al proposed the novel concepts related to MCDM methods to enhance and support the theory of decision-making including [47,48]. In order to handle this kind of decision-making problems, in this article, we introduce the concept of mHF-sets with an associated novel approach of TOPSIS for MCGDM problems.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
