Hamacher heronian mean operators for multi-critria decision-making under multi-valued picture fuzzy uncertain lingsuitic environment

Article type: Research Article

Authors: Li, Baolin | Yang, Lihua^{; *}

Affiliations: School of Economics and Management, HubeiUniversity of Automotive Technology, Shiyan, Hubei, China

Correspondence: [*] Corresponding author. Lihua Yang. E-mail: [email protected].

Abstract: Picture fuzzy set (PFS) and linguistic term set (LTS) are two significant notions in multi-criteria decision-making (MCDM). In practice, decision-makers sometimes need utilize the multiple probable membership degrees for an uncertain linguistic term to express evaluation information. Motivated by these, to better convey the vagueness and uncertainty of cognitive information, multi-valued picture fuzzy uncertain linguistic set combining picture hesitant fuzzy set with uncertain linguistic term set is proposed. We firstly define the concepts of multi-valued picture fuzzy uncertain linguistic set and multi-valued picture fuzzy uncertain linguistic number. Hamacher operations are more general and flexible in information fusion, thus, Hamacher operations and comparison method are developed at the same time. Improved generalized Heronian Mean operator can simultaneously reflect correlations between values and prevent the redundant calculation. Then, two operators of improved generalized weighted Heronian mean and improved generalized geometric weighted Heronian mean in view of Hamacher operations are proposed. Meanwhile, some distinguished properties and instances of two operators are explored as well. Moreover, a novel MCDM approach applying the developed operators is constructed. Ultimately, an illustrative example on vendor selection is performed, and sensitivity analysis and comparison analysis are provided to verify the powerfulness of the proposed method.

Keywords: Hamacher, improved generalized heronian operator, multi-criteria decision-making, multi-valued picture fuzzy uncertain linguistic set

DOI: 10.3233/JIFS-210404

Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1531-1552, 2021