AbstractThis paper studies the heterogeneous fixed fleet vehicle routing problem (HFFVRP), in which the fleet is composed of a fixed number of vehicles with different capacities, fixed costs, and variable costs. Given the fleet composition, the HFFVRP is to determine a vehicle scheduling strategy with the objective of minimizing the total transportation cost. We propose a multistart adaptive memory programming (MAMP) and path relinking algorithm to solve this problem. Through the search memory, MAMP at each iteration constructs multiple provisional solutions, which are further improved by a modified tabu search. As an intensification strategy, path relinking is integrated to enhance the performance of MAMP. We conduct a series of experiments to evaluate and demonstrate the effectiveness of the proposed algorithm.


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    Titel :

    An adaptive memory programming metaheuristic for the heterogeneous fixed fleet vehicle routing problem


    Beteiligte:
    Li, Xiangyong (Autor:in) / Tian, Peng (Autor:in) / Aneja, Y.P. (Autor:in)


    Erscheinungsdatum :

    2010-02-03


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch