• DocumentCode
    2558233
  • Title

    An improved species conserving genetic algorithm for multimodal optimization

  • Author

    Dingcai Shen ; Xia, Xuewen

  • Author_Institution
    Sch. of Comput. & Inf. Sci., Hubei Eng. Univ., Xiaogan, China
  • fYear
    2012
  • fDate
    29-31 May 2012
  • Firstpage
    1156
  • Lastpage
    1160
  • Abstract
    A new method for finding multiple solutions of multimodal optimization problems is proposed in this paper. To avoid the necessity of specifying a niche radius, the proposed method adopts hybrid of species conservation and hill-valley detection mechanism. The proposed method is compared with classical Species Conservation Genetic Algorithm (SCGA) on a number of standard benchmark problems. The experimental results show that the new approach performs better in finding all optima with no additional parameters introduced.
  • Keywords
    genetic algorithms; SCGA; hill-valley detection mechanism; multimodal optimization; niche radius; species conservation genetic algorithm; Algorithm design and analysis; Educational institutions; Evolutionary computation; Genetic algorithms; Optimization; Radio frequency; Standards; Genetic Algorithm; Hill-valley Detecting; Multimodal Optimization; Species Conservation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2012 Eighth International Conference on
  • Conference_Location
    Chongqing
  • ISSN
    2157-9555
  • Print_ISBN
    978-1-4577-2130-4
  • Type

    conf

  • DOI
    10.1109/ICNC.2012.6234613
  • Filename
    6234613