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A new hybrid genetic algorithm for the capacitated vehicle routing problem

Author

Listed:
  • J Berger

    (Defence Research and Development Canada - Valcartier)

  • M Barkaoui

    (Defence Research and Development Canada - Valcartier)

Abstract

Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. A new hybrid genetic algorithm to address the capacitated VRP is proposed. The basic scheme consists in concurrently evolving two populations of solutions to minimize total travelled distance using genetic operators combining variations of key concepts inspired from routing techniques and search strategies used for a time variant of the problem to further provide search guidance while balancing intensification and diversification. Results from a computational experiment over common benchmark problems report the proposed approach to be very competitive with the best-known methods.

Suggested Citation

  • J Berger & M Barkaoui, 2003. "A new hybrid genetic algorithm for the capacitated vehicle routing problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(12), pages 1254-1262, December.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:12:d:10.1057_palgrave.jors.2601635
    DOI: 10.1057/palgrave.jors.2601635
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    References listed on IDEAS

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    Cited by:

    1. Gong, Manlin & Hu, Yucong & Chen, Zhiwei & Li, Xiaopeng, 2021. "Transfer-based customized modular bus system design with passenger-route assignment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    2. István Borgulya, 2008. "An algorithm for the capacitated vehicle routing problem with route balancing," 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. 16(4), pages 331-343, December.
    3. Hao Zhang & Yan Cui & Hepu Deng & Shuxian Cui & Huijia Mu, 2021. "An Improved Genetic Algorithm for the Optimal Distribution of Fresh Products under Uncertain Demand," Mathematics, MDPI, vol. 9(18), pages 1-18, September.
    4. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.
    5. F Alonso & M J Alvarez & J E Beasley, 2008. "A tabu search algorithm for the periodic vehicle routing problem with multiple vehicle trips and accessibility restrictions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(7), pages 963-976, July.
    6. A A Juan & J Faulin & J Jorba & D Riera & D Masip & B Barrios, 2011. "On the use of Monte Carlo simulation, cache and splitting techniques to improve the Clarke and Wright savings heuristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1085-1097, June.
    7. Jose Escribano Macias & Nils Goldbeck & Pei-Yuan Hsu & Panagiotis Angeloudis & Washington Ochieng, 2020. "Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1089-1125, December.
    8. Guido Perboli & Ferdinando Pezzella & Roberto Tadei, 2008. "EVE-OPT: a hybrid algorithm for the capacitated vehicle routing problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 68(2), pages 361-382, October.
    9. Jin Qin & Yong Ye & Bi-rong Cheng & Xiaobo Zhao & Linling Ni, 2017. "The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments," Sustainability, MDPI, vol. 9(2), pages 1-24, February.

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    Keywords

    vehicle routing problems; heuristics;

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