• DocumentCode
    1643606
  • Title

    Random search with species conservation for multimodal functions

  • Author

    Li, J.P. ; Wood, A.

  • Author_Institution
    Sch. of Eng. Design & Technol., Univ. of Bradford, Bradford
  • fYear
    2009
  • Firstpage
    3164
  • Lastpage
    3171
  • Abstract
    This paper is to investigate the influence of a minimum population size on the performance of the species conservation technique in searching multiple solutions. The species conservation technique is combined a random search technique, which is a special genetic algorithm with one individual, to present an algorithm, called species conservation random search (SCRS), for solving multimodal problems. Each species is built around a dominating point, called the species seed, with a given species radius, and the species are saved in the species set. The random search is used to explore a new point in the neighborhood area of an initial point randomly selected from the species set. A modified species conservation technique has been developed to update species seeds according to these new exploration points. Numerical experiments demonstrate that the proposed SCRS is very effective in dealing with multimodal problems and can also find all the global solutions of test functions.
  • Keywords
    biology; genetic algorithms; random processes; modified species conservation technique; multimodal functions; species conservation random search; species conservation technique; species radius; species seed; Algorithm design and analysis; Biological system modeling; Evolution (biology); Genetic algorithms; Optimization methods; Particle swarm optimization; Simulated annealing; Space exploration; Testing; Thyristors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983344
  • Filename
    4983344