Highlights Modeling a novel sustainable hub location–allocation problem. Proposing a mixed possibilistic–stochastic programming approach. Developing two tailored meta-heuristics to solve large size instances. Proposing a new continuous solution representation for SHLP.

    Abstract This paper addresses a novel sustainable hub location problem (SHLP) in which two new environmental-based cost functions accounting for air and noise pollution of vehicles are incorporated. To cope with uncertain data incorporated in the model, a mixed possibilistic–stochastic programming approach is proposed to construct the crisp counterpart. A simulated annealing (SA) and an imperialist competitive algorithm (ICA) with a new solution representation are developed to solve real-sized instances whose performances are compared with a proposed lower bound. Finally, some computational experiments are provided to demonstrate the effectiveness of the proposed model and solution approaches.


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    Title :

    Sustainable hub location under mixed uncertainty


    Contributors:


    Publication date :

    2013-12-11


    Size :

    27 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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