• DocumentCode
    2567089
  • Title

    Population distributions in biogeography-based optimization algorithms with elitism

  • Author

    Simon, Dan ; Ergezer, Mehmet ; Du, Dawei

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Cleveland State Univ., Cleveland, OH, USA
  • fYear
    2009
  • fDate
    11-14 Oct. 2009
  • Firstpage
    991
  • Lastpage
    996
  • Abstract
    Biogeography-based optimization (BBO) is an evolutionary algorithm that is based on the science of biogeography. Biogeography is the study of the geographical distribution of organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration between islands. This paper develops a Markov analysis of BBO, including the option of elitism. Our analysis gives the probability of BBO convergence to each possible population distribution for a given problem. We compare our BBO Markov analysis with a similar genetic algorithm (GA) Markov analysis. Analytical comparisons on three simple problems show that with high mutation rates the performance of GAs and BBO is similar, but with low mutation rates BBO outperforms GAs. Our analysis also shows that elitism is not necessary for all problems, but for some problems it can significantly improve performance.
  • Keywords
    Markov processes; biology; genetic algorithms; probability; Markov analysis; biogeography-based optimization algorithm; evolutionary algorithm; genetic algorithm; geographical organism distribution; island; population distribution; probability; Algorithm design and analysis; Biogeography; Cybernetics; Evolutionary computation; Genetic algorithms; Genetic mutations; Intersymbol interference; Mathematical model; Performance analysis; USA Councils; Markov analysis; biogeography-based optimization; combinatorics; evolutionary algorithms; probability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1062-922X
  • Print_ISBN
    978-1-4244-2793-2
  • Electronic_ISBN
    1062-922X
  • Type

    conf

  • DOI
    10.1109/ICSMC.2009.5346058
  • Filename
    5346058