Hybrid meta-heuristics with VNS and exact methods: alication to large unconditional and conditional vertex $$$$-centre roblems |
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| Authors: | Chandra Ade Irawan Said Salhi Zvi Drezner |
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| Institution: | 1.Centre for Operational Research and Logistics (CORL), Department of Mathematics,University of Portsmouth,Lion Terrace,UK;2.Department of Industrial Engineering,Institut Teknologi Nasional,Bandung,Indonesia;3.Centre for Logistics & Heuristic Optimization (CLHO),Kent Business School, University of Kent,Canterbury,UK;4.Department of Information Systems and Decision Sciences, Steven G. Mihaylo College of Business and Economis,California State University-Fullerton,Fullerton,USA |
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| Abstract: | Large-scale unconditional and conditional vertex \(p\)-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with \(p\) varying from 5 to 100. To the best of our knowledge, these are the largest instances solved for unconditional and conditional vertex \(p\)-centre problems. The two proposed meta-heuristics yield competitive results for both classes of problems. |
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