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

Chandra Ade Irawan (), Said Salhi and Zvi Drezner
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Chandra Ade Irawan: University of Portsmouth
Said Salhi: Kent Business School, University of Kent
Zvi Drezner: California State University-Fullerton

Journal of Heuristics, 2016, vol. 22, issue 4, No 8, 507-537

Abstract: Abstract Large-scale unconditional and conditional vertex $$p$$ 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 $$p$$ p varying from 5 to 100. To the best of our knowledge, these are the largest instances solved for unconditional and conditional vertex $$p$$ p -centre problems. The two proposed meta-heuristics yield competitive results for both classes of problems.

Keywords: Large unconditional and conditional vertex $$p$$ p -centre; Aggregation; Variable neighbourhood search; Exact method (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10732-014-9277-7

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