• DocumentCode
    1526419
  • Title

    Markov Models for Biogeography-Based Optimization

  • Author

    Simon, Dan ; Ergezer, Mehmet ; Du, Dawei ; Rarick, Rick

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Cleveland State Univ., Cleveland, OH, USA
  • Volume
    41
  • Issue
    1
  • fYear
    2011
  • Firstpage
    299
  • Lastpage
    306
  • Abstract
    Biogeography-based optimization (BBO) is a population-based evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the science and study of the geographical distribution of biological organisms. In BBO, problem solutions are analogous to islands, and the sharing of features between solutions is analogous to the migration of species. This paper derives Markov models for BBO with selection, migration, and mutation operators. Our models give the theoretically exact limiting probabilities for each possible population distribution for a given problem. We provide simulation results to confirm the Markov models.
  • Keywords
    Markov processes; ecology; evolutionary computation; mathematical operators; Markov model; biogeography based optimization; biological organism; geographical distribution; mutation operator; population based evolutionary algorithm; probability distribution; Biogeography; Biological system modeling; Biological systems; Convergence; Evolutionary computation; Genetic algorithms; Genetic mutations; H infinity control; Mathematics; Simulated annealing; Biogeography-based optimization (BBO); Markov models; evolutionary algorithms (EAs); Algorithms; Biological Evolution; Computer Simulation; Cybernetics; Geography; Markov Chains; Models, Biological;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1083-4419
  • Type

    jour

  • DOI
    10.1109/TSMCB.2010.2051149
  • Filename
    5497206