Cross-docking is one of the lean logistics tools that is used for uniting the shipments during the loops replacement. Cross-docking is the process of product movement form distribution centers without storage function. Vehicle routing problem in Cross-Dock external environment has much influence on cross-dock costs. This paper provides a model for minimizing total distance traveled by vehicles in the external environment of a cross-dock. In this paper, Vehicles routes was modeled with capacitated vehicle routing problem (CVRP) and genetic algorithm (GA) was used to solve the model. To validate responses obtained by GA, simulated annealing (SA) was used. Also, to evaluate the efficacy of two algorithms (SA & GA) in different CVRP problems in cross-dock, 10 problems with different dimensions are evaluated. The results show that in problems with smaller size GA is more efficient, whereas in large size problems SA is more efficient


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    Titel :

    Vehicle routing problem in cross-dock using genetic algorithm, Case: Iran Khodro company.


    Beteiligte:
    Ahmad Jafarian (Autor:in) / Maghsod Amiri (Autor:in) / Laya Olfat (Autor:in)


    Erscheinungsdatum :

    2017




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt






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