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
Link To Document :
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