A group multi-criteria decision-making based on best-worst method. (December 2018)

• Record Type: Journal Article
• Authors: Safarzadeh, Soroush; Khansefid, Saba; Rasti-Barzoki, Morteza
• Is Part Of: Computers & industrial engineering. Volume 126(2018)
• Page Start: 111
• Page End: 121
• Publication Date: 2018-12
• Subjects: Multi-criteria decision-making -- Group decision-making -- Best-worst method -- Group-AHP; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.09.011
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Proposing a novel group-based decision-making method according to BWM called GBWM. Considering two various model in the proposed method for different kind of problems. Analyzing the main results of some group decision problems with GBWM. Applying the proposed models to select the best piping method, as a case study. Abstract: In recent years, the daily increase in the application of the group decision-making approaches can be seen in the various areas such as facility location, supplier selection, energy schemes, project management, and performance evaluation. The group decision-making methods aggregate the individual preferences and present the best agreement using the mathematical models. On the other hand, best-worst method (BWM) is a novel multi-attribute decision-making (MADM) method which can solve the decision problems by a new perspective on the pairwise comparisons. So, in this paper, we extend a novel group decision-making method based on BWM (GBWM), which includes new attributes, under the three steps. Also, for the first time, we formulate two various mathematical models ( M1 and M2 ) to calculate the optimal weights of the criteria. Then, we present some numerical instances to evaluate the proposed method and clarify how we can use it. In addition, we perform a comprehensive sensitivity analysis on the main parameters of the proposed method. Finally, we use GBWM to solve a real case study. The results show the acceptable performance of GBWM, besides the simple usage and the customization ability of the presented model.