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Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems

Author

Listed:
  • Olivera Janković

    (University of Kragujevac
    University of Belgrade)

  • Stefan Mišković

    (University of Belgrade)

  • Zorica Stanimirović

    (University of Belgrade)

  • Raca Todosijević

    (LAMIH UMR CNRS 8201 - Universié de Valenciennes
    Serbian Academy of Sciences and Arts)

Abstract

This paper deals with uncapacitated single and multiple allocation p-hub maximal covering problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We present new mixed-integer programming formulations of the considered problems, which are valid for both binary and partial coverage cases. The efficiency of the proposed formulations is evaluated through computational experiments on smaller-size instances, and compared with the state-of-the art models from the literature. The obtained results indicate that the new UMApHMCP formulation outperforms the existing one for both coverage criteria in the sense of solutions’ quality and running times. In order to solve instances of larger problem dimension, we develop two heuristic methods based on variable neighborhood search: general VNS (GVNS) for USApHMCP and basic VNS (BVNS) for UMApHMCP. The proposed GVNS and BVNS involve the same shaking procedure in order to hopefully escape local minima traps, while local search phases in GVNS and BVNS use different neighborhood structures in accordance with applied allocation schemes. Computational experiments conducted on smaller-size instances showed that both GVNS and BVNS almost instantly reach all known optimal solutions. In addition, the proposed GVNS and BVNS showed to be very efficient when solving large and large-scale hub instances with up to 1000 nodes, which were not previously considered as test instances for the considered problems. Both GVNS and BVNS provided best solutions on challenging USApHMCP and UMApHMCP instances for both coverage cases in short running times, which indicates their potential to be applied to similar problems.

Suggested Citation

  • Olivera Janković & Stefan Mišković & Zorica Stanimirović & Raca Todosijević, 2017. "Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems," Annals of Operations Research, Springer, vol. 259(1), pages 191-216, December.
    • Handle: RePEc:spr:annopr:v:259:y:2017:i:1:d:10.1007_s10479-017-2508-1
    DOI: 10.1007/s10479-017-2508-1
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    Cited by:

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    2. G. Bergantiños & J. Vidal-Puga, 2020. "One-way and two-way cost allocation in hub network problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 199-234, March.
    3. A. Ghodratnama & H. R. Arbabi & A. Azaron, 2020. "A bi˗objective hub location-allocation model considering congestion," Operational Research, Springer, vol. 20(4), pages 2427-2466, December.
    4. Madani, Seyed Reza & Shahandeh Nookabadi, Ali & Hejazi, Seyed Reza, 2018. "A bi-objective, reliable single allocation p-hub maximal covering location problem: Mathematical formulation and solution approach," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 118-136.
    5. Li, Yanfeng & Liu, Yang, 2021. "The static bike rebalancing problem with optimal user incentives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    6. Lazar Mrkela & Zorica Stanimirović, 2022. "A variable neighborhood search for the budget-constrained maximal covering location problem with customer preference ordering," Operational Research, Springer, vol. 22(5), pages 5913-5951, November.

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