Abstract

Hesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.

Highlights

  • In multicriteria decision-making (MCDM) problems, we need to choose the best alternative/alternatives according to several determined criteria from a set of alternatives [1,2,3]

  • The primary contributions of this study are summarized as follows: 1. Consistency measures from the perspectives of additive/ multiplicatively consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced, which integrate the advantages of Hesitant fuzzy preference relations (HFPRs) and best worst method (BWM)

  • Several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs

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Summary

Introduction

In multicriteria decision-making (MCDM) problems, we need to choose the best alternative/alternatives according to several determined criteria from a set of alternatives [1,2,3]. We first introduce the concepts of additive/ multiplicatively consistent HFBWPRs and develop several programming models for deriving priority weight vectors from the proposed HFBWPRs, which include two cases.

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