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
Link To Document