The competitive facility location problem under disruption risks |
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| Affiliation: | 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;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. Department of Information Systems and Mathematical Sciences, Nanzan University, Japan;2. College of Business Administration, University of Missouri – St. Louis, USA;3. IITB-Monash Research Academy, IIT Bombay, Powai, Mumbai 400076, India;4. CSIRO Mathematical and Information Sciences, Australia;5. Department of Mechanical and Aerospace Engineering, Clayton, VIC 3800, Australia;1. Department of Statistics and Operations Research, University of Vienna, Austria;2. Institute for Water Quality, Resource and Waste Management, Vienna University of Technology, Austria;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 |
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| Abstract: | Two players sequentially locate a fixed number of facilities, competing to capture market share. Facilities face disruption risks, and each customer patronizes the nearest operational facility, regardless of who operates it. The problem therefore combines competitive location and location with disruptions. This combination has been absent from the literature. We model the problem as a Stackelberg game in which the leader locates facilities first, followed by the follower, and formulate the leader’s decision problem as a bilevel optimization problem. A variable neighborhood decomposition search heuristic which includes variable fixing and cut generation is developed. Computational results suggest that high quality solutions can be found quickly. Interesting managerial insights are drawn. |
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| Keywords: | Competitive location Facility disruptions Bilevel optimization Local search Variable neighborhood search |
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