Highlights Study the urban delivery problem considering uncertain assembly time. Formulate the problem to a chance-constrained programming problem. An algorithm consisting of two sub-heuristics is proposed to solve the problem. Comprehensive numerical experiments with real dataset are performed.

    Abstract This paper studies a stochastic programming problem to minimize the total completion time consists of the travel time and the assembly time, for a new class of urban delivery problems. The problem is formulated into a chance-constrained programming problem and the probability distribution characteristics of the uncertainty of product assembly time are obtained using a statistical learning method. Then the original chance-constrained programming problem can be converted into an equivalent deterministic programming problem. Subsequently, an algorithm consisting of two sub-heuristics is proposed to solve the deterministic problem. Finally, comprehensive numerical experiments with real dataset show the superiority of the model and the algorithm.


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    Title :

    Minimizing the total completion time of an urban delivery problem with uncertain assembly time


    Contributors:
    Liu, Bingbing (author) / Guo, Xiaolong (author) / Yu, Yugang (author) / Zhou, Qiang (author)


    Publication date :

    2019-11-03


    Size :

    20 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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