• DocumentCode
    2538285
  • Title

    A Hybrid BPSO Approach for Fuzzy Facility Location Problems with VaR

  • Author

    Wang, Shuming ; Watada, Junzo

  • Author_Institution
    Grad. Sch. of IPS, Waseda Univ., Kitakyushu, Japan
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    43
  • Lastpage
    46
  • Abstract
    In this paper, a fuzzy facility location model with Value at Risk (VaR) is proposed, which is a two-stage fuzzy zero-one integer programming. Since the fuzzy parameters of the location problem are continuous fuzzy variables with an infinite support, the computation of VaR is inherently an infinite-dimensional optimization problem, which can not be solved analytically. In order to solve the model, first of all, the objective function VaR is approximated through discretization method of fuzzy variables. Therefore, the original problem is converted to the task of a finite-dimensional optimization. Then, a hybrid heuristic algorithm integrating binary particle swarm optimization (BPSO), simplex algorithm and the approximation approach is designed to solve the location model. Finally, a numerical example is provided.
  • Keywords
    facility location; fuzzy set theory; integer programming; particle swarm optimisation; VaR; approximation approach; binary particle swarm optimization; continuous fuzzy variable; discretization method; finite dimensional optimization; fuzzy facility location problem; hybrid BPSO approach; hybrid heuristic algorithm; infinite dimensional optimization problem; objective function; simplex algorithm; two stage fuzzy zero one integer programming; value at risk; Algorithm design and analysis; Approximation algorithms; Approximation methods; Computational modeling; Optimization; Particle swarm optimization; Programming; Binary particle swarm optimization; Facility location; Fuzzy variable; Two-stage fuzzy programming; Value at Risk;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-1-4244-8891-9
  • Electronic_ISBN
    978-0-7695-4281-2
  • Type

    conf

  • DOI
    10.1109/ICGEC.2010.19
  • Filename
    5715366