In this paper, the dynamic warehouse location problem is considered. A Tabu search algorithm (TSA) is proposed to solve the problem. The procedure is tested on three generated benchmark problems. The small-sized problem includes 25 customers, 3 potential warehouse locations, and 3 planning horizon periods. The medium-sized problem consists of 50 customers, 5 potential warehouse locations, and 5 periods of the planning horizon. The large-sized problem consists of 100 customers, 10 potential warehouse locations, and 10 periods of the planning horizon. The proposed algorithm was compared with a solution method for mixed-integer linear programming in a cloud, CPLEX. The proposed algorithm provides reasonable solutions, while CPLEX could not provide solutions for medium and large problems in the limited computation time.


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    Titel :

    Optimizing Dynamic Warehouse Location Problems Using a Stochastic Search


    Beteiligte:


    Erscheinungsdatum :

    25.08.2023


    Format / Umfang :

    446709 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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