• DocumentCode
    3281163
  • Title

    A New Approach for Solving Linear Bilevel Programming Using Differential Evolution

  • Author

    Kejia Pan ; Yan Yang ; Jianli Liu

  • Author_Institution
    Key Lab. of Metallogenic Prediction of Nonferrous Metals, Central South Univ., Changsha, China
  • fYear
    2012
  • fDate
    25-28 Aug. 2012
  • Firstpage
    453
  • Lastpage
    456
  • Abstract
    In this paper, a differential evolution (DE) algorithm is developed for solving the linear bilevel programming (LBP) problem. by use of Kuhn-Tucker conditions of the lower level programming problem, the LBP is transferred into a single level programming which can be solved by DE algorithm. This DE algorithm avoids the use of penalty function to deal with the constrains, by changing the randomly generated initial population into an initial population satisfying the constraints in order to improve the ability of the DE to deal with the constrains. the performance of the proposed approach is ascertained by comparing the results with GA and PSO using two problems in the literature.
  • Keywords
    evolutionary computation; linear programming; particle swarm optimisation; DE; GA; Kuhn-Tucker conditions; LBP; PSO; differential evolution; linear bilevel programming; lower level programming problem; penalty function; randomly generated initial population; Genetic algorithms; Linear programming; Programming profession; Sociology; Statistics; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
  • Conference_Location
    Kitakushu
  • Print_ISBN
    978-1-4673-2138-9
  • Type

    conf

  • DOI
    10.1109/ICGEC.2012.24
  • Filename
    6456886