Highlights We provide worst-case results for the optimal Min-Expected Value policy. We provide worst-case results for the optimal Min–Max policy. We formulate a dynamic programming model of the Min–Max problem. We apply an Exact DP algorithm to compare the two policies. We design a Min–Max Matheuristic algorithm to find near-optimal policies. We provide a lower bound on the optimal Min–Max cost.

    Abstract We study the problem in which one supplier delivers a product to a set of retailers over time by using an outsourced fleet of vehicles. Since the probability distribution of the demand is not known, we provide a Min–Max approach to find robust policies. We show that the optimal Min-Expected Value policy can be very poor in the worst case. We provide a Min–Max Dynamic Programming formulation that allows us to exactly solve the problem in small instances. Finally, we implement a Min–Max Matheuristic to solve benchmark instances and show that it is very effective.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Min–Max exact and heuristic policies for a two-echelon supply chain with inventory and transportation procurement decisions


    Beteiligte:
    Bertazzi, Luca (Autor:in) / Bosco, Adamo (Autor:in) / Laganà, Demetrio (Autor:in)


    Erscheinungsdatum :

    2016-05-14


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch