• DocumentCode
    2986094
  • Title

    Uniform Design Based Hybrid Genetic Algorithm for Multiobjective Bilevel Convex Programming

  • Author

    Jia, Liping ; Wang, Yuping ; Fan, Lei

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an, China
  • fYear
    2011
  • fDate
    3-4 Dec. 2011
  • Firstpage
    159
  • Lastpage
    163
  • Abstract
    Multiobjective bilevel linear programming is a decentralized decision problem, it consists of many objectives at the upper level and the lower level, respectively. It has a wide field of applications and has been proven to be NP-hard. In this paper, a kind of multiobjective bilevel convex programming(MBCP) is studied, in which the lower level is first transformed into an equivalent single objective bilevel convex programming problem by weighted aggregation method. Then, for the equivalent problem, we use uniform design scheme to generate some representative weight vectors. Thereafter, a crossover operator and mutation operator are designed. Based on all these, a uniform design based hybrid genetic algorithm is proposed for MBCP. Finally, the performance of the proposed algorithm is illustrated by two numerical experiments. The results (including the compared results) show that the proposed algorithm is effective.
  • Keywords
    computational complexity; convex programming; decision making; genetic algorithms; linear programming; NP-hard; decentralized decision problem; multiobjective bilevel convex programming; multiobjective bilevel linear programming; uniform design based hybrid genetic algorithm; weighted aggregation method; Algorithm design and analysis; Educational institutions; Genetic algorithms; Pareto optimization; Programming; Vectors; Multiobjective bilevel convex programming; hybrid genetic algorithm; numerical experiment; uniform design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
  • Conference_Location
    Hainan
  • Print_ISBN
    978-1-4577-2008-6
  • Type

    conf

  • DOI
    10.1109/CIS.2011.43
  • Filename
    6128096