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Open AccessArticle

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

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Department of Industrial Engineering and Management, Mehran University of Engineering and Technology, Jamshoro, Sindh 76062, Pakistan
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Department of Garment Manufacturing, National Textile University, Faisalabad 37610, Pakistan
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Department of Industrial and Manufacturing Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan
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Department of Industrial Engineering, Hongik University, Seoul 04066, Korea
*
Authors to whom correspondence should be addressed.
Mathematics 2019, 7(2), 137; https://doi.org/10.3390/math7020137
Received: 24 December 2018 / Revised: 21 January 2019 / Accepted: 25 January 2019 / Published: 1 February 2019
Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company. View Full-Text
Keywords: resilient supply chain; supplier selection; fuzzy optimization; disruption risks resilient supply chain; supplier selection; fuzzy optimization; disruption risks
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MDPI and ACS Style

Mari, S.I.; Memon, M.S.; Ramzan, M.B.; Qureshi, S.M.; Iqbal, M.W. Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain. Mathematics 2019, 7, 137.

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