Partitioned fuzzy measure-based linear assignment method for Pythagorean fuzzy multi-criteria decision-making with a new likelihood

Decui Liang, Adjei Peter Darko, Zeshui Xu and Yinrunjie Zhang

Journal of the Operational Research Society, 2020, vol. 71, issue 5, 831-845

Abstract: The aim of this paper is to develop an extended linear assignment method to solve multi-criteria decision-making (MCDM) problems under the Pythagorean fuzzy environment, where the criteria values take the form of the Pythagorean fuzzy numbers (PFNs) and the information about criteria weights are correlative. In order to obtain the criteria-wise rankings of the linear assignment method, we firstly define a new likelihood for the comparison between PFNs. Then, we introduce the fuzzy measure to determine the weighted-rank frequency matrix of the linear assignment method. Unlike the existing literature of the fuzzy measure, this paper incorporates the partitioned structure of the criteria set into it and proposes a new partitioned fuzzy measure. Further, we design the extended linear assignment method by using the new likelihood of PFNs and partitioned fuzzy measure for Pythagorean fuzzy multi-criteria decision-making (PFMCDM). Finally, a practical example is used to illustrate and verify our proposed method.

Date: 2020
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DOI: 10.1080/01605682.2019.1590133

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