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A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem

Author

Listed:
  • Subramanian, Anand
  • Penna, Puca Huachi Vaz
  • Uchoa, Eduardo
  • Ochi, Luiz Satoru

Abstract

This paper deals with the Heterogeneous Fleet Vehicle Routing Problem (HFVRP). The HFVRP generalizes the classical Capacitated Vehicle Routing Problem by considering the existence of different vehicle types, with distinct capacities and costs. The objective is to determine the best fleet composition as well as the set of routes that minimize the total costs. The proposed hybrid algorithm is composed by an Iterated Local Search (ILS) based heuristic and a Set Partitioning (SP) formulation. The SP model is solved by means of a Mixed Integer Programming solver that interactively calls the ILS heuristic during its execution. The developed algorithm was tested in benchmark instances with up to 360 customers. The results obtained are quite competitive with those found in the literature and new improved solutions are reported.

Suggested Citation

  • Subramanian, Anand & Penna, Puca Huachi Vaz & Uchoa, Eduardo & Ochi, Luiz Satoru, 2012. "A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 221(2), pages 285-295.
  • Handle: RePEc:eee:ejores:v:221:y:2012:i:2:p:285-295
    DOI: 10.1016/j.ejor.2012.03.016
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    References listed on IDEAS

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    1. Liu, Shuguang & Huang, Weilai & Ma, Huiming, 2009. "An effective genetic algorithm for the fleet size and mix vehicle routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 434-445, May.
    2. Renaud, Jacques & Boctor, Fayez F., 2002. "A sweep-based algorithm for the fleet size and mix vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 140(3), pages 618-628, August.
    3. Li, Xiangyong & Tian, Peng & Aneja, Y.P., 2010. "An adaptive memory programming metaheuristic for the heterogeneous fixed fleet vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 1111-1127, November.
    4. Y H Lee & J I Kim & K H Kang & K H Kim, 2008. "A heuristic for vehicle fleet mix problem using tabu search and set partitioning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 833-841, June.
    5. Tarantilis, C. D. & Kiranoudis, C. T. & Vassiliadis, V. S., 2004. "A threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 152(1), pages 148-158, January.
    6. C.D. Tarantilis & C.T. Kiranoudis, 2002. "BoneRoute: An Adaptive Memory-Based Method for Effective Fleet Management," Annals of Operations Research, Springer, vol. 115(1), pages 227-241, September.
    7. Imran, Arif & Salhi, Said & Wassan, Niaz A., 2009. "A variable neighborhood-based heuristic for the heterogeneous fleet vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 197(2), pages 509-518, September.
    8. C D Tarantilis & C T Kiranoudis & V S Vassiliadis, 2003. "A list based threshold accepting metaheuristic for the heterogeneous fixed fleet vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 65-71, January.
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