Solving multifacility Huff location models on networks using metaheuristic and exact approaches |
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| Affiliation: | 1. Mathematical Institute SANU, Belgrade, Serbia;2. University of Seville, Seville, Spain;1. Department of Mechanics of Materials and Structures, School of Mechanical Engineering, Hanoi University of Science and Technology, No. 1, Dai Co Viet Road, Hanoi, Viet Nam;2. Department of Biomedical Engineering and Mechanics, M/C 0219, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;1. Dipartimento di Matematica e Informatica, Università di Cagliari, Cagliari, Italy;2. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, Università della Calabria and the Institute of High Performance Computing and Networking of the National Research Council of Italy, Via Pietro Bucci 42C, 87036 Rende (CS), Italy;3. Software Department, N.I. Lobachevskiy University of Nizhni Novgorod, Gagarin Av. 23, Nizhni Novgorod, Russia;1. State Key laboratory of Fine Chemicals, School of Chemistry, Dalian University of Technology, Dalian 116024, China;2. School Petroleum and Chemical Engineering, Dalian University of Technology, Panjin Campus, Panjin 124221, China;3. Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2–4 Hibikino, Wakamatsu, Kitakyushu, Fukuoka 808-0196, Japan;1. College of Urban and Environment Sciences, Liaoning Normal University, No.850 Huanghe Road, Dalian 116029, China;2. College of Urban and Environment Sciences, Peking University, No.5 Yiheyuan Road, Beijing 100871, China;3. Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, No.850 Huanghe Road, Dalian 116029, China |
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| Abstract: | In this paper we consider multifacility Huff facility location problem on networks. First, we introduce a slight modification of the existing mixed integer nonlinear mathematical model and confirm its validity by using the solver for nonlinear optimization, KNITRO. Second, since the problem is NP-hard, we develop three methods that are based on three metaheuristic principles: Variable Neighborhood Search, Simulated Annealing, and Multi-Start Local Search. Based on extensive computational experiments on large size instances (up to 800 customers and 100 potential facilities), it appears that VNS based heuristic outperforms the other two proposed methods. |
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| Keywords: | Location Networks Competitive location Metaheuristics Variable Neighborhood Search |
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