• DocumentCode
    2225931
  • Title

    A new non-redundant objective set generation algorithm in many-objective optimization problems

  • Author

    Guo, Xiaofang ; Wang, Yuping ; Wang, Xiaoli ; Wei, Jingxuan

  • Author_Institution
    School of Computer Science and Technology, Xidian University
  • fYear
    2015
  • fDate
    25-28 May 2015
  • Firstpage
    2851
  • Lastpage
    2858
  • Abstract
    Among the many-objective optimization problems, there exists a kind of problem with redundant objectives, it is possible to design effective algorithms by removing the redundant objectives and keeping the non-redundant objectives so that the original problem becomes the one with much fewer objectives. In this paper, a new non-redundant objective set generation algorithm is proposed. To do so, first, a multi-objective evolutionary algorithm based decomposition is adopted to generate a small number of representative non-dominated solutions widely distributed on the Pareto front. Then, the conflicting objective pairs are identified through these non-dominated solutions, and the non-redundant objective set is determined by these pairs. Finally, the experiments are conducted on a set of benchmark test problems and the results indicate the effectiveness and efficiency of the proposed algorithm.
  • Keywords
    Algorithm design and analysis; Approximation algorithms; Object recognition; Pareto optimization; Sociology; Evolutionary Algorithm; conflicting objectives; many-objective optimization; non-redundant objective set; objective reduction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2015 IEEE Congress on
  • Conference_Location
    Sendai, Japan
  • Type

    conf

  • DOI
    10.1109/CEC.2015.7257243
  • Filename
    7257243