Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study |
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| Institution: | 1. Institute of Transport and Logistics Studies, The University of Sydney, Darlington, NSW 2008, Australia;2. Department of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran;3. Department of Business Administration, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Raipei 10016, Taiwan, R.O.C.;1. Department of Industrial & Operations Engineering, The University of Michigan, Ann Arbor, MI 48109, United States;2. Department of Industrial & Manufacturing Engineering, The Iowa State University, Ames, IA 50011, United States |
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| Abstract: | A mixed-integer, non-linear model is developed for designing robust global supply chain networks under uncertainty. Six resilience strategies are proposed to mitigate the risk of correlated disruptions. In addition, an efficient parallel Taguchi-based memetic algorithm is developed that incorporates a customized hybrid parallel adaptive large neighborhood search. Fitness landscape analysis is used to determine an effective selection of neighborhood structures, while the upper bound found by Lagrangian relaxation heuristic is used to evaluate quality of solutions and effectiveness of the proposed metaheuristic. The model is solved for a real-life case of a global medical device manufacturer to extract managerial insights. |
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| Keywords: | Global supply chain network design Robust optimization Resilience strategies Disruption management Parallel memetic algorithm Fitness landscape analysis |
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