Aiming at the vehicle routing problem (VRP) in modern logistics system, this paper proposes a multi-constraint vehicle routing problem optimization model with time window, considering the diversity of cargo circulation and vehicle transportation efficiency, allowing vehicles to disperse operation at nodes and improve the transportation performance. In this paper, the improved honey badger algorithm (IHBA) is adopted to introduce Cubic chaotic mapping and random perturbation strategy, and the elite tangent search and differential variation strategy are adopted to enhance the global search and avoid premature convergence.IHBA Validates Potential to Solve Complex Vehicle routing Problems and Demonstrates Theoretical Practical Value of VRP Research and Logistics and Distribution at CEC2017.


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    Titel :

    Multi-constraint vehicle routing problem based on improved honey badger algorithm


    Beteiligte:
    Zhang, Weishan (Herausgeber:in) / Lu, Qinghua (Herausgeber:in) / Li, Chunxiao (Autor:in) / Zhou, Lei (Autor:in) / Wang, Suxin (Autor:in)

    Kongress:

    Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024) ; 2024 ; Qingdao, China


    Erschienen in:

    Proc. SPIE ; 13416


    Erscheinungsdatum :

    08.11.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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