Optimizing vehicle routing is a key step to reduce the carbon emissions in the transportation industry, which is an important goal for achieving national sustainable development. So multi-objective vehicle routing problem is studied under low carbon emission. In this paper, we propose a multi-objective mixed-integer programming model to minimize the number of vehicles, travel distance, and carbon emission costs by considering each vehicle's loading capacity and the number of customers served. The NSGA-II is designed for solving the model, and the effectiveness of the algorithm is verified by the actual example of the SH logistics company. It is shown that the carbon emission costs are reduced by 2.45%, and the total travel distance is reduced by 14.21% after comparing the optimized result and the former one. The research results of this paper provide a decision basis for logistics companies to plan routes under a low-carbon background.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-Objective Vehicle Routing Problem Based on NSGA-II


    Contributors:
    Mengyue, Yang (author) / Keping, Li (author)


    Publication date :

    2020-09-27


    Size :

    4104523 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Multi-objective classification based on NSGA-II

    Zhao, Binping / Xue, Yu / Xu, Bin et al. | British Library Online Contents | 2018


    Multi-Objective Vehicle Routing Problem in Hazardous Material Transportation

    Zheng, B. / American Society of Civil Engineers | British Library Conference Proceedings | 2010


    Optimization of Vehicle Routing Problem Based on Multi-Objective Genetic Algorithm

    Zhong, R. / Wu, J.P. / Du, Y.M. | British Library Conference Proceedings | 2013


    A Multi-Objective Solution of Green Vehicle Routing Problem

    Kabadurmuş Özgür / Erdoğan Mehmet Serdar / Özkan Yiğitcan et al. | DOAJ | 2019

    Free access