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MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems

Author

Listed:
  • Angel Juan
  • Javier Faulin
  • Albert Ferrer
  • Helena Lourenço
  • Barry Barrios
Abstract
This paper discusses the use of probabilistic or randomized algorithms for solving vehicle routing problems with non-smooth objective functions. Our approach employs non-uniform probability distributions to add a biased random behavior to the well-known savings heuristic. By doing so, a large set of alternative good solutions can be quickly obtained in a natural way and without complex configuration processes. Since the solution-generation process is based on the criterion of maximizing the savings, it does not need to assume any particular property of the objective function. Therefore, the procedure can be especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods—both of exact and approximate nature—may fail to reach their full potential. The results obtained so far are promising enough to suggest that the idea of using biased probability distributions to randomize classical heuristics is a powerful one that can be successfully applied in a variety of cases. Copyright Sociedad de Estadística e Investigación Operativa 2013

Suggested Citation

  • Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    • Handle: RePEc:spr:topjnl:v:21:y:2013:i:1:p:109-132
    DOI: 10.1007/s11750-011-0245-1
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    3. Alejandro Estrada-Moreno & Albert Ferrer & Angel A. Juan & Javier Panadero & Adil Bagirov, 2020. "The Non-Smooth and Bi-Objective Team Orienteering Problem with Soft Constraints," Mathematics, MDPI, vol. 8(9), pages 1-16, September.
    4. Eskandarpour, Majid & Ouelhadj, Djamila & Hatami, Sara & Juan, Angel A. & Khosravi, Banafsheh, 2019. "Enhanced multi-directional local search for the bi-objective heterogeneous vehicle routing problem with multiple driving ranges," European Journal of Operational Research, Elsevier, vol. 277(2), pages 479-491.
    5. Christian Fikar & Angel A. Juan & Enoc Martinez & Patrick Hirsch, 2016. "A discrete-event driven metaheuristic for dynamic home service routing with synchronised trip sharing," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(3), pages 323-340.
    6. Arnau, Quim & Barrena, Eva & Panadero, Javier & de la Torre, Rocio & Juan, Angel A., 2022. "A biased-randomized discrete-event heuristic for coordinated multi-vehicle container transport across interconnected networks," European Journal of Operational Research, Elsevier, vol. 302(1), pages 348-362.
    7. Lorena Reyes-Rubiano & Laura Calvet & Angel A. Juan & Javier Faulin & Lluc Bové, 2020. "A biased-randomized variable neighborhood search for sustainable multi-depot vehicle routing problems," Journal of Heuristics, Springer, vol. 26(3), pages 401-422, June.
    8. Jian Li & Yang Li & Panos M. Pardalos, 2016. "Multi-depot vehicle routing problem with time windows under shared depot resources," Journal of Combinatorial Optimization, Springer, vol. 31(2), pages 515-532, February.
    9. Oscar Dominguez & Angel A. Juan & Barry Barrios & Javier Faulin & Alba Agustin, 2016. "Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet," Annals of Operations Research, Springer, vol. 236(2), pages 383-404, January.
    10. Christian Fikar & Patrick Hirsch, 2018. "Evaluation of trip and car sharing concepts for home health care services," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 78-97, June.
    11. Juan F. Gomez & Javier Panadero & Rafael D. Tordecilla & Juliana Castaneda & Angel A. Juan, 2022. "A Multi-Start Biased-Randomized Algorithm for the Capacitated Dispersion Problem," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
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    13. Jesica Armas & Luis Cadarso & Angel A. Juan & Javier Faulin, 2017. "A multi-start randomized heuristic for real-life crew rostering problems in airlines with work-balancing goals," Annals of Operations Research, Springer, vol. 258(2), pages 825-848, November.

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