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Parallel Single and Multiple Objectives Genetic Algorithms: A Survey

Author

Listed:
  • 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)

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.

Suggested Citation

  • B. S. P. Mishra & S. Dehuri & R. Mall & A. Ghosh, 2011. "Parallel Single and Multiple Objectives Genetic Algorithms: A Survey," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 2(2), pages 21-57, April.
  • Handle: RePEc:igg:jaec00:v:2:y:2011:i:2:p:21-57
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