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

Author

Listed:
  • Chandra Ade Irawan

    (University of Portsmouth
    Institut Teknologi Nasional)

  • Said Salhi

    (Kent Business School, University of Kent)

  • Zvi Drezner

    (California State University-Fullerton)

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.

Suggested Citation

  • Chandra Ade Irawan & Said Salhi & Zvi Drezner, 2016. "Hybrid meta-heuristics with VNS and exact methods: application to large unconditional and conditional vertex $$p$$ p -centre problems," Journal of Heuristics, Springer, vol. 22(4), pages 507-537, August.
  • Handle: RePEc:spr:joheur:v:22:y:2016:i:4:d:10.1007_s10732-014-9277-7
    DOI: 10.1007/s10732-014-9277-7
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    References listed on IDEAS

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    Cited by:

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    3. Cihan Çetinkaya & Samer Haffar, 2018. "A Risk-Based Location-Allocation Approach for Weapon Logistics," Logistics, MDPI, vol. 2(2), pages 1-15, May.

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