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Hybrid meta-heuristics with VNS and exact methods: application to large unconditional and conditional vertex p-centre problems

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 technique...

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Published in:Journal of heuristics 2016-08, Vol.22 (4), p.507-537
Main Authors: Irawan, Chandra Ade, Salhi, Said, Drezner, Zvi
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description 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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subjects Algorithms
Artificial Intelligence
Calculus of Variations and Optimal Control
Optimization
Customers
Heuristic
Management Science
Mathematics
Mathematics and Statistics
Methods
Neighborhoods
Operations Research
Operations Research/Decision Theory
title Hybrid meta-heuristics with VNS and exact methods: application to large unconditional and conditional vertex p-centre problems
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