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Green Supplier Selection Using Improved TOPSIS and Best-Worst Method Under Intuitionistic Fuzzy Environment
Volume 29, Issue 4 (2018), pp. 773–800
Pub. online: 1 January 2018      Type: Research Article      Open accessOpen Access
Received
1 June 2017
Accepted
1 July 2018
Published
1 January 2018

Abstract

Green supplier selection has recently become one of the key strategic considerations in green supply chain management, due to regulatory requirements and market trends. It can be regarded as a multi-criteria group decision-making (MCGDM) problem, in which a set of alternatives are evaluated with respect to multiple criteria. MCGDM methods based on Analytic Hierarchy Process (AHP) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are widely used in solving green supplier selection problems. However, the classic AHP must conduct large amounts of pairwise comparisons to derive a consistent result due to its complex structure. Meanwhile, the classic TOPSIS only considers one single negative idea solution in selecting suppliers, which is insufficiently cautious. In this study, an improved TOPSIS integrated with Best-Worst Method (BWM) is developed to solve MCGDM problems with intuitionistic fuzzy information in the context of green supplier selection. The BWM is investigated to derive criterion weights, and the improved TOPSIS method is proposed to obtain decision makers’ weights in terms of different criteria. Moreover, the developed TOPSIS-based coefficient is used to rank alternatives. Finally, a green supplier selection problem in the agri-food industry is presented to validate the proposed approach followed by sensitivity and comparative analyses.

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Biographies

Tian Zhang-Peng

Z.P. Tian received his MS degree in management science and engineering form Central South University, Changsha, China, in 2016. He is currently working towards the PhD degree at the Business School, Central South University. His current research interests include decision-making theory and application, risk management and control, and information management.

Zhang Hong-Yu

H.Y. Zhang received the MS degree in computer software and theory and the PhD degree in management science and engineering from Central South University, Changsha, China, in 2005 and 2009, respectively. She is currently an associate professor at the Business School, Central South University. Her research interests include information management and its applications in production operations. Her current research focuses on remanufacturing production management and decision-making theory.

Wang Jian-Qiang
jqwang@csu.edu.cn

J.Q. Wang received the PhD degree in management science and engineering from Central South University, Changsha, China, in 2005. He is currently a professor at the Business School, Central South University. His current research interests include decision-making theory and application, risk management and control, and information management.

Wang Tie-Li

T.L. Wang received the PhD degree in management science and engineering from Central South University, Changsha, China, in 2007. She is currently a professor at Management School, University of South China. His current research interests include decision-making theory and application, risk management and control, and nuclear emergency decision-making.


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Keywords
supplier selection group decision-making best-worst method intuitionistic fuzzy sets

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