Abstract To get global solution in multi-depots vehicle transshipment scheduling problem (MDVTSP), MDVTSP models are established. Genetic algorithm and particle swarm hybrid optimization is established to solve MDVTSP. The optimization course is as follow: first set up chromosome vector to get goods’ transshipment point, and assign goods to vehicles. Second, establish tabu matrix for ant colony optimization (ACO) to get vehicle route. Then evaluate and filtrate vehicle scheduling results by optimization aim, circulate until meet terminate qualification. Illustration results show that Hybrid arithmetic is effective for multi-depots vehicle transshipment scheduling problem.


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    Titel :

    Study on Multi-depots Vehicle Transshipment Scheduling Problem and Its Genetic Algorithm and Ant Colony Algorithm Hybrid Optimization


    Beteiligte:
    Wang, Lei-zhen (Autor:in) / Wang, Ding-wei (Autor:in) / Wu, Si-lei (Autor:in) / Wang, Si-han (Autor:in) / Wang, Su-xin (Autor:in)


    Ausgabe :

    1st ed. 2016


    Erscheinungsdatum :

    01.01.2016


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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