An extension of the best-worst method based on the spherical fuzzy sets for multi-criteria decision-making

Gholamreza Haseli; Reza Sheikh; Saeid Jafarzadeh Ghoushchi; Mostafa Hajiaghaei-Keshteli; Sarbast Moslem; Muhammet Deveci; Seifedine Kadry

doi:10.1007/s41066-024-00462-w

An extension of the best-worst method based on the spherical fuzzy sets for multi-criteria decision-making

Granul Comput. 2024;9(2):40. doi: 10.1007/s41066-024-00462-w. Epub 2024 Mar 30.

Authors

Gholamreza Haseli^{1

2}, Reza Sheikh³, Saeid Jafarzadeh Ghoushchi⁴, Mostafa Hajiaghaei-Keshteli¹, Sarbast Moslem², Muhammet Deveci^{5

6

7}, Seifedine Kadry^{8

9

10}

Affiliations

¹ Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico.
² School of Architecture Planning and Environmental Policy, University College Dublin, Belfield, Dublin, D04 V1W8 Ireland.
³ Faculty of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran.
⁴ Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran.
⁵ Department of Industrial Engineering, Turkish Naval Academy, National Defence University, 34942 Tuzla, Istanbul, Turkey.
⁶ The Bartlett School of Sustainable Construction, University College London, 1-19 Torrington Place, London, WC1E 7HB UK.
⁷ Department of Electronical and Computer Engineering, Lebanese American University, Byblos, Lebanon.
⁸ Department of Applied Data Science, Noroff University College, Kristiansand, Norway.
⁹ Artificial Intelligence Research Center (AIRC), Ajman University, 346 Ajman, United Arab Emirates.
¹⁰ MEU Research Unit, Middle East University, Amman, 11831 Jordan.

Abstract

The ambiguous information in multi-criteria decision-making (MCDM) and the vagueness of decision-makers for qualitative judgments necessitate accurate tools to overcome uncertainties and generate reliable solutions. As one of the latest and most powerful MCDM methods for obtaining criteria weight, the best-worst method (BWM) has been developed. Compared to other MCDM methods, such as the analytic hierarchy process, the BWM requires fewer pairwise comparisons and produces more consistent results. Consequently, the main objective of this study is to develop an extension of BWM using spherical fuzzy sets (SFS) to address MCDM problems under uncertain conditions. Hesitancy, non-membership, and membership degrees are three-dimensional functions included in the SFS. The presence of three defined degrees allows decision-makers to express their judgments more accurately. An optimization model based on nonlinear constraints is used to determine optimal spherical fuzzy weight coefficients (SF-BWM). Additionally, a consistency ratio is proposed for the SF-BWM to assess the reliability of the proposed method in comparison to other versions of BWM. SF-BWM is examined using two numerical decision-making problems. The results show that the proposed method based on the SF-BWM provided the criteria weights with the same priority as the BWM and fuzzy BWM. However, there are differences in the criteria weight values based on the SF-BWM that indicate the accuracy and reliability of the obtained results. The main advantage of using SF-BWM is providing a better consistency ratio. Based on the comparative analysis, the consistency ratio obtained for SF-BWM is threefold better than the BWM and fuzzy BWM methods, which leads to more accurate results than BWM and fuzzy BWM.

Keywords: Best–worst method; Consistency ratio; Fuzzy set; Multi-criteria decision-making; Spherical fuzzy sets.