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


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  • Li, Xiangyong
  • Tian, Peng
  • Aneja, Y.P.
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    This 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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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.

    Volume (Year): 46 (2010)
    Issue (Month): 6 (November)
    Pages: 1111-1127

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    Handle: RePEc:eee:transe:v:46:y:2010:i:6:p:1111-1127

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    Keywords: Vehicle routing Heterogeneous fixed fleet Adaptive memory programming Path relinking Metaheuristic;


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    Cited by:
    1. 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.
    2. Subramanian, Anand & Penna, Puca Huachi Vaz & Uchoa, Eduardo & Ochi, Luiz Satoru, 2012. "A hybrid algorithm for the Heterogeneous Fleet Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 221(2), pages 285-295.
    3. 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.


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