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http://dx.doi.org/10.3745/JIPS.04.0118

Supplier Evaluation in Green Supply Chain: An Adaptive Weight D-S Theory Model Based on Fuzzy-Rough-Sets-AHP Method  

Li, Lianhui (Ningxia Key Laboratory of Intelligent Information and Big Data Processing, North Minzu University)
Xu, Guanying (Ningxia Key Laboratory of Intelligent Information and Big Data Processing, North Minzu University)
Wang, Hongguang (The 713th Research Institute of China Shipbuilding Industry Corporation)
Publication Information
Journal of Information Processing Systems / v.15, no.3, 2019 , pp. 655-669 More about this Journal
Abstract
Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.
Keywords
Adaptive Weight; D-S Theory; Fuzzy-Rough-Sets-AHP; Green Supply Chain; Supplier Evaluation;
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