• DocumentCode
    3576753
  • Title

    Multi-objective genetic algorithm in green just-in-time logistics

  • Author

    Memari, Ashkan ; Rahim, Abd Rahman Abdul ; Ahmad, Robiah

  • Author_Institution
    Dept. of Mater., Manuf. & Ind. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
  • fYear
    2014
  • Firstpage
    1239
  • Lastpage
    1243
  • Abstract
    This paper addresses a mixed-integer linear programming model by integrating just-in-time delivery along with green objectives in a logistics network. Multi-objective genetic algorithm optimization has been applied in order to minimize the number of delivery and lead-time as well as environmental impact of logistic network. This evolutionary based algorithm incorporates non-dominated sorting genetic algorithm, so as to allow heuristic for parallel optimization of the objective functions. Computational results demonstrate efficiency of the proposed model for minimizing the objective functions. Finally, the conclusion and some areas of further research are proposed.
  • Keywords
    environmental factors; genetic algorithms; integer programming; just-in-time; linear programming; logistics; environmental impact; evolutionary based algorithm; green just-in-time logistics; green objectives; just-in-time delivery; lead time; logistic network; logistics network; mixed integer linear programming model; multiobjective genetic algorithm optimization; nondominated sorting genetic algorithm; parallel optimization; Carbon dioxide; Green products; Mathematical model; Optimization; Supply chains; Green supply chain; NSGA II; multi objective optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/IEEM.2014.7058836
  • Filename
    7058836