Retail supply chain network design under operational and disruption risks |
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| Institution: | 1. Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 48109, USA;2. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;1. Department of Logistics Engineering and Management, Lingnan (University) College, Sun Yat-Sen University, PR China;2. Department of Industrial Engineering and Logistics Management, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR, PR China;1. Enterprise and Logistics Engineering, Florida International University, 10555 W Flagler Street, Room 3114, Miami, FL 33174, USA;2. TCS Digital Manufacturing and Operations (DMO) Innovation Program, Tata Consultancy Services, 1000 Summit Drive, Milford, OH 45150, USA;3. The Systems Realization Laboratory, 202 W. Boyd Street, Room 116-G, The University of Oklahoma, Norman, OK 73019, USA;4. The Systems Realization Laboratory, 865 Asp Avenue, Room 306, The University of Oklahoma, Norman, OK 73019, USA;1. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran;2. Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran;1. School of Transportation and Civil Engineering, School of Economics, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China;2. School of Economics, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China |
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| Abstract: | Designing robust and resilient retail networks under operational and disruption risks can create substantial competitive advantage. In this paper, a deterministic multiple set-covering model is first proposed. Then, it is extended to a possibilistic scenario-based robust model by scenario generation and disruption profiling to design a robust and resilient retail network. The developed models are validated through randomly generated examples and a real case study in retailing. Numerical results demonstrate that designing retail chains without considering operational and disruption risks is really misleading. Also, multiple covering of retail stores as the measure of redundancy increases the network’s resilience significantly. |
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| Keywords: | Retail network design Resilience Robustness Possibilistic scenario-based robust programming |
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