Highlights A new stochastic IRP with partial distributional information on demands is studied. A distributionally robust model with a probabilistic objective function is proposed. The sample average approximation method and a hierarchical approach are proposed.

    Abstract This paper studies a stochastic inventory routing problem with alternative handling modules and limited capital budget, under partial distributional information (i.e., the mean and covariance matrix of customer demands). The objective is to maximize the service level, i.e., the probability of jointly ensuring no stockout and respecting the warehouse capacities for all customers at the end of each period. A novel distributionally robust chance constrained formulation is proposed. The sample average approximation method and a model-based hierarchical approach based on problem analysis are developed. Computational results show that the latter approach is more efficient. We also draw some managerial insights.


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    Title :

    Distributionally robust inventory routing problem to maximize the service level under limited budget


    Contributors:
    Liu, Ming (author) / Liu, Xin (author) / Chu, Feng (author) / Zheng, Feifeng (author) / Chu, Chengbin (author)


    Publication date :

    2019-04-18


    Size :

    22 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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