• DocumentCode
    2219975
  • Title

    Exponentially decreased dimension number strategy based dynamic search fireworks algorithm for solving CEC2015 competition problems

  • Author

    Zheng, Shaoqiu ; Yu, Chao ; Li, Junzhi ; Tan, Ying

  • Author_Institution
    Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, 100871, P.R. China
  • fYear
    2015
  • fDate
    25-28 May 2015
  • Firstpage
    1083
  • Lastpage
    1090
  • Abstract
    Fireworks algorithm (FWA) is one swarm intelligence algorithm proposed in 2010, which takes the inspiration from the firework explosion process. Compared with other meta-heuristic algorithms, FWA presents a cooperative explosive search manner. In the explosive search manner, the explosion amplitudes, explosion sparks´ numbers and explosion dimension selection methods play the key roles for its successful implementation. In this paper, the performance analyses of the different explosion dimension number strategies in FWA and its variants are presented at first, then the exponentially decreased explosion dimension number strategy is introduced for the most recent dynamic search fireworks algorithm (dynFWA), called ed-dynFWA, to enhance its local search ability. To validate the performance of ed-dynFWA, it is used to participate in the CEC 2015 competition for solving learning based optimization problems.
  • Keywords
    Algorithm design and analysis; Explosives; Heuristic algorithms; Optimization; Silicon; Sparks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2015 IEEE Congress on
  • Conference_Location
    Sendai, Japan
  • Type

    conf

  • DOI
    10.1109/CEC.2015.7257010
  • Filename
    7257010