• DocumentCode
    2404879
  • Title

    Multi-Objective Fixed-Charged Transportation Optimization in Supply Chain Management

  • Author

    Hongwei, Zhang ; Xiaoke, Cui ; Shurong, Zou

  • Author_Institution
    Sch. of Comput. Sci., Chengdu Univ. of Inf. Technol., Chengdu, China
  • fYear
    2010
  • fDate
    7-9 May 2010
  • Firstpage
    3247
  • Lastpage
    3250
  • Abstract
    For coping with the multi-objective fixed-charged transportation optimization problem (mfcTP) in SCM a new fuzzy rules-based particle swarm optimization algorithm called Fuzzy-PSO is proposed in the paper. In terms of this new algorithm base on the fitness vector function, we firstly construct the fuzzy rule base which is convenient to express the explicit knowledge, and then apply the fuzzy rulers to control the process of traffic distribution with the fixed-charged. The experimental results show that it can find better Pareto front and Pareto optimal solutions in the real-world problems even if nonlinear and discontinuous. So it is more effective than st-GA and m-GA.
  • Keywords
    Pareto optimisation; fuzzy set theory; genetic algorithms; particle swarm optimisation; supply chain management; transportation; Pareto optimal solution; fitness vector function; fuzzy rules based particle swarm optimization algorithm; multiobjective fixed charged transportation optimization; process control; supply chain management; traffic distribution; Availability; Monitoring; Optimization; Particle swarm optimization; Presses; Production facilities; Transportation; PSO; Pareto front; Pruefer number; fitness vector function; fuzzy rules; mfcTP;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Business and E-Government (ICEE), 2010 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3997-3
  • Type

    conf

  • DOI
    10.1109/ICEE.2010.817
  • Filename
    5591100