An adaptive memory programming metaheuristic for the heterogeneous fixed fleet vehicle routing problem
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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Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.
Volume (Year): 46 (2010)
Issue (Month): 6 (November)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description
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- 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.
- 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.
- 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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