This study aims to investigate the green vehicle routing problem (GVRP), which considers stochastic traffic speeds, so that fuel consumption and emissions can be reduced. Considering a heterogeneous fleet, the fuel consumption rate differs due to several factors, such as vehicle types and conditions, travel speeds, roadway gradients, and payloads. A mathematical model was proposed to deal with the GVRP, and its objective is to minimize the sum of the fixed costs and the expected fuel consumption costs. A customized genetic algorithm was proposed for solving the model. The computational experiments confirm the efficiency of the algorithm and show that the solution of GVRP is quite different from that of the traditional vehicle routing problem. The proposed model and algorithm are capable of suggesting a guidance for green logistics service providers to adopt a beneficial vehicle routing plan so as to eventually achieve a low economic and environmental cost.


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    Title :

    The Green Vehicle Routing Problem with Stochastic Travel Speeds


    Contributors:

    Conference:

    16th COTA International Conference of Transportation Professionals ; 2016 ; Shanghai, China


    Published in:

    Publication date :

    2016-07-01




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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