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A general variable neighborhood search for solving the multi-objective open vehicle routing problem

Author

Listed:
  • Jesús Sánchez-Oro

    (Rey Juan Carlos University)

  • Ana D. López-Sánchez

    (Pablo de Olavide University)

  • J. Manuel Colmenar

    (Rey Juan Carlos University)

Abstract

The multi-objective open vehicle routing problem (MO-OVRP) is a variant of the classic vehicle routing problem in which routes are not required to return to the depot after completing their service and where more than one objective is optimized. This work is intended to solve a more realistic and general version of the problem by considering three different objective functions. MO-OVRP seeks solutions that minimize the total number of routes, the total travel cost, and the longest route. For this purpose, we present a general variable neighborhood search algorithm to approximate the efficient set. The performance of the proposal is supported by an extensive computational experimentation which includes the comparison with the well-known multi-objective genetic algorithm NSGA-II.

Suggested Citation

  • Jesús Sánchez-Oro & Ana D. López-Sánchez & J. Manuel Colmenar, 2020. "A general variable neighborhood search for solving the multi-objective open vehicle routing problem," Journal of Heuristics, Springer, vol. 26(3), pages 423-452, June.
  • Handle: RePEc:spr:joheur:v:26:y:2020:i:3:d:10.1007_s10732-017-9363-8
    DOI: 10.1007/s10732-017-9363-8
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    References listed on IDEAS

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    1. Pierre Hansen & Nenad Mladenović & Raca Todosijević & Saïd Hanafi, 2017. "Variable neighborhood search: basics and variants," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 423-454, September.
    2. Z Fu & R Eglese & L Y O Li, 2005. "A new tabu search heuristic for the open vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(3), pages 267-274, March.
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    4. N. Norouzi & R. Tavakkoli-Moghaddam & M. Ghazanfari & M. Alinaghian & A. Salamatbakhsh, 2012. "A New Multi-objective Competitive Open Vehicle Routing Problem Solved by Particle Swarm Optimization," Networks and Spatial Economics, Springer, vol. 12(4), pages 609-633, December.
    5. C D Tarantilis & G Ioannou & C T Kiranoudis & G P Prastacos, 2005. "Solving the open vehicle routeing problem via a single parameter metaheuristic algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 588-596, May.
    6. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    7. López-Sánchez, A.D. & Hernández-Díaz, A.G. & Vigo, D. & Caballero, R. & Molina, J., 2014. "A multi-start algorithm for a balanced real-world Open Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 238(1), pages 104-113.
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    Cited by:

    1. Daqing Wu & Chenxiang Wu, 2022. "Research on the Time-Dependent Split Delivery Green Vehicle Routing Problem for Fresh Agricultural Products with Multiple Time Windows," Agriculture, MDPI, vol. 12(6), pages 1-28, May.

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