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Tabu search variants for the mix fleet vehicle routing problem

Author

Listed:
  • N A Wassan

    (University of Kent at Canterbury)

  • I H Osman

    (American University of Beirut)

Abstract

The Mix Fleet Vehicle Routing Problem (MFVRP) involves the design of a set of minimum cost routes, originating and terminating at a central depot, for a fleet of heterogeneous vehicles with various capacities, fixed costs and variable costs to service a set of customers with known demands. This paper develops new variants of a tabu search meta-heuristic for the MFVRP. These variants use a mix of different components, including reactive tabu search concepts; variable neighbourhoods, special data memory structures and hashing functions. The reactive concept is used in a new way to trigger the switch between simple moves for intensification and more complex ones for diversification of the search strategies. The special data structures are newly introduced to efficiently search the various neighbourhood spaces. The combination of data structures and strategic balance between intensification and diversification generates an efficient and robust implementation, which is very competitive with other algorithms in the literature on a set of benchmark instances for which some new best-known solutions are provided.

Suggested Citation

  • N A Wassan & I H Osman, 2002. "Tabu search variants for the mix fleet vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(7), pages 768-782, July.
  • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:7:d:10.1057_palgrave.jors.2601344
    DOI: 10.1057/palgrave.jors.2601344
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    Citations

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    Cited by:

    1. C-H Lan & C-C Chen, 2007. "Optimal purchase of two-itemized drugs for a disease," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(3), pages 309-316, March.
    2. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.
    3. Niaz A. Wassan & A. Hameed Wassan & Gábor Nagy, 2008. "A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries," Journal of Combinatorial Optimization, Springer, vol. 15(4), pages 368-386, May.
    4. 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.
    5. Puca Huachi Vaz Penna & Anand Subramanian & Luiz Satoru Ochi & Thibaut Vidal & Christian Prins, 2019. "A hybrid heuristic for a broad class of vehicle routing problems with heterogeneous fleet," Annals of Operations Research, Springer, vol. 273(1), pages 5-74, February.
    6. Brandão, José, 2009. "A deterministic tabu search algorithm for the fleet size and mix vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 195(3), pages 716-728, June.
    7. N Wassan, 2007. "Reactive tabu adaptive memory programming search for the vehicle routing problem with backhauls," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1630-1641, December.
    8. Belfiore, PatrI´cia & Yoshida Yoshizaki, Hugo Tsugunobu, 2009. "Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil," European Journal of Operational Research, Elsevier, vol. 199(3), pages 750-758, December.
    9. Patrícia Belfiore & Luiz Fávero, 2007. "Scatter search for the fleet size and mix vehicle routing problem with time windows," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 15(4), pages 351-368, November.
    10. Mehdi Nourinejad & Matthew J. Roorda, 2017. "A continuous approximation model for the fleet composition problem on the rectangular grid," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 373-401, March.
    11. Liu, Shuguang, 2013. "A hybrid population heuristic for the heterogeneous vehicle routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 54(C), pages 67-78.
    12. I H Osman & S Ahmadi, 2007. "Guided construction search metaheuristics for the capacitated p-median problem with single source constraint," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(1), pages 100-114, January.
    13. Salhi, Said & Wassan, Niaz & Hajarat, Mutaz, 2013. "The Fleet Size and Mix Vehicle Routing Problem with Backhauls: Formulation and Set Partitioning-based Heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 22-35.
    14. N A Wassan, 2006. "A reactive tabu search for the vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 111-116, January.
    15. 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.
    16. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "Thirty years of heterogeneous vehicle routing," European Journal of Operational Research, Elsevier, vol. 249(1), pages 1-21.

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