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Tabu search for a multi-objective routing problem

Author

Listed:
  • J Pacheco

    (Universidad de Burgos)

  • R Martí

    (Universitat de València)

Abstract

Multi-objective optimization problems deal with the presence of different conflicting objectives. Given that it is not possible to obtain a single solution by optimizing all the objectives simultaneously, a common way to face these problems is to obtain a set of efficient solutions called the non-dominated frontier. In this paper, we address the problem of routing school buses with two objectives: minimize the number of buses, and minimize the longest time a student would have to stay in the bus. The trade-off in this problem is between service level, which is represented by the maximum route length, and operational cost, which is represented by the number of buses in the solution. We present different constructive solution methods and a tabu search procedure to obtain non-dominated solutions. The procedure is coupled with an intensification phase based on the path relinking methodology: a strategy proposed several years ago, which has been rarely used in actual implementations. Computational experiments with real data, in the context of routing school buses in a rural area, establish the effectiveness of our procedure in relation to the approach previously identified to be the best.

Suggested Citation

  • J Pacheco & R Martí, 2006. "Tabu search for a multi-objective routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 29-37, January.
  • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:1:d:10.1057_palgrave.jors.2601917
    DOI: 10.1057/palgrave.jors.2601917
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    References listed on IDEAS

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    1. A Corberán & E Fernández & M Laguna & R Martí, 2002. "Heuristic solutions to the problem of routing school buses with multiple objectives," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(4), pages 427-435, April.
    2. Éric Taillard & Philippe Badeau & Michel Gendreau & François Guertin & Jean-Yves Potvin, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 31(2), pages 170-186, May.
    3. Lawrence D. Bodin & Lon Berman, 1979. "Routing and Scheduling of School Buses by Computer," Transportation Science, INFORMS, vol. 13(2), pages 113-129, May.
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    Citations

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    Cited by:

    1. Shafahi, Ali & Wang, Zhongxiang & Haghani, Ali, 2018. "SpeedRoute: Fast, efficient solutions for school bus routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 473-493.
    2. Chi Ming Tam & Thomas Tong & Bill Wong, 2007. "An integrated system for earthmoving planning," Construction Management and Economics, Taylor & Francis Journals, vol. 25(11), pages 1127-1137.
    3. Jose Gonzalez-Velarde & Salvador Garcia-Lumbreras & Alberto Garcia-Diaz, 2008. "A multi-stop routing problem," Annals of Operations Research, Springer, vol. 157(1), pages 153-167, January.
    4. Ellegood, William A. & Solomon, Stanislaus & North, Jeremy & Campbell, James F., 2020. "School bus routing problem: Contemporary trends and research directions," Omega, Elsevier, vol. 95(C).
    5. P. Matl & R. F. Hartl & T. Vidal, 2018. "Workload Equity in Vehicle Routing Problems: A Survey and Analysis," Transportation Science, INFORMS, vol. 52(2), pages 239-260, March.
    6. Wang, Zhongxiang & Haghani, Ali, 2020. "Column generation-based stochastic school bell time and bus scheduling optimization," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1087-1102.
    7. Ellegood, William A. & Campbell, James F. & North, Jeremy, 2015. "Continuous approximation models for mixed load school bus routing," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 182-198.
    8. Nicolas Jozefowiez & Gilbert Laporte & Frédéric Semet, 2012. "A Generic Branch-and-Cut Algorithm for Multiobjective Optimization Problems: Application to the Multilabel Traveling Salesman Problem," INFORMS Journal on Computing, INFORMS, vol. 24(4), pages 554-564, November.
    9. Huasheng Liu & Yuqi Zhao & Jin Li & Yu Li & Xiaowen Li & Sha Yang, 2022. "A Two-Phase, Joint-Commuting Model for Primary and Secondary Schools Considering Parking Sharing," IJERPH, MDPI, vol. 19(11), pages 1-25, May.
    10. Ansari, Azadeh & Farrokhvar, Leily & Kamali, Behrooz, 2021. "Integrated student to school assignment and school bus routing problem for special needs students," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    11. C Alabas-Uslu, 2008. "A self-tuning heuristic for a multi-objective vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(7), pages 988-996, July.
    12. Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
    13. Fátima M. Souza Lima & Davi S. D. Pereira & Samuel V. Conceição & Ricardo S. Camargo, 2017. "A multi-objective capacitated rural school bus routing problem with heterogeneous fleet and mixed loads," 4OR, Springer, vol. 15(4), pages 359-386, December.

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