Parallel Single and Multiple Objectives Genetic Algorithms: A Survey

B. S. P. Mishra, S. Dehuri, R. Mall and A. Ghosh
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B. S. P. Mishra: KIIT University, India
S. Dehuri: Fakir Mohan University, India
R. Mall: Indian Institute of Technology Kharagpur, India
A. Ghosh: Indian Statistical Institute, India

International Journal of Applied Evolutionary Computation (IJAEC), 2011, vol. 2, issue 2, 21-57

Abstract: This paper critically reviews the reported research on parallel single and multi-objective genetic algorithms. Many early efforts on single and multi-objective genetic algorithms were introduced to reduce the processing time needed to reach an acceptable solution. However, some parallel single and multi-objective genetic algorithms converged to better solutions as compared to comparable sequential single and multiple objective genetic algorithms. The authors review several representative models for parallelizing single and multi-objective genetic algorithms. Further, some of the issues that have not yet been studied systematically are identified in the context of parallel single and parallel multi-objective genetic algorithms. Finally, some of the potential applications of parallel multi-objective GAs are discussed.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaec00:v:2:y:2011:i:2:p:21-57

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