This paper considers a multi-period and product inventory-routing problem. This model involves two levels, namely, a distributor and several retailers. This problem is modeled with the aim of minimizing bi-objectives, namely, the total cost of the system (including start-up, distribution, and maintenance costs) and risk-based transportation. Products are delivered to retailers by some heterogeneous vehicles with specific capacities through a direct delivery strategy, and inventory shortage is assumed to be impermissible. To validate this new bi-objective model, the ε-constraint method is used to solve problems. Because problems without distribution planning are very complex to solve optimally, the problem considered in this paper is also Non-deterministic Polynomial (NP-hard). Therefore, a nondominated sorting genetic algorithm (NSGA-II) and a multi-objective imperialist competitive algorithm (MOICA) are used and developed to solve a number of test problems. Furthermore, the computational results are compared and the performance of the foregoing algorithms is analyzed.


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    Titel :

    Bi-objective inventory routing problem with backhauls under transportation risks: two meta-heuristics


    Beteiligte:
    Arab, R. (Autor:in) / Ghaderi, S.F. (Autor:in) / Tavakkoli-Moghaddam, R. (Autor:in)

    Erschienen in:

    Transportation Letters ; 12 , 2 ; 113-129


    Erscheinungsdatum :

    07.02.2020


    Format / Umfang :

    17 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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