A metaheuristic approach to the reliable location routing problem under disruptions |
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| Institution: | 1. Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China;2. Department of Industrial Engineering, Tsinghua University, Beijing 100084, China;3. Department of Systems & Industrial Engineering, The University of Arizona, Tucson, AZ 85721, USA;1. Faculty of Engineering, Universidad Diego Portales, Chile;2. PhD student at Research Centre for Operations Management, University of Leuven, Belgium;3. Transport Engineering Consultant at Steer Davies Gleave, Chile;1. Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China;2. Department of Industrial Engineering, Tsinghua University, Beijing 100084, China;1. Research Center on Modern Logistics, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China;2. Department of Industrial Engineering, Tsinghua University, Beijing 100084, China;3. Department of Mathematics and Industrial Engineering and CIRRELT, Polytechnique Montréal and CIRRELT, Montréal H3C 3A7, Canada;1. Harbin Institute of Technology, Harbin, Heilongjiang 150001, China;2. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA;3. Center for Advanced Infrastructure and Transportation, Rutgers, The State University of New Jersey, NJ 08854, USA;4. School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA;1. Zhejiang Cainiao Supply Chain Management Co., Ltd., Hangzhou 310000, China;2. Department of Industrial Engineering, Tsinghua University, Beijing 100084, China;3. Department of Industrial and Systems Engineering, Lehigh University, 200 West Packer Ave., Mohler Lab, Bethlehem, PA 18015, USA;4. Department of Transportation Engineering, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China |
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| Abstract: | This paper examines a reliable capacitated location–routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn. |
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| Keywords: | Location–routing problem Facility disruptions Reliability design Simulated annealing |
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