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Multi-Objective Genetic Algorithm with Strategies for Dying of Solution

Author

Listed:
  • Rahila Patel

    (Research scholar, G. H. Raisoni College of Engineering, Nagpur, India)

  • M. M. Raghuwanshi

    (Principal, Rajiv Gandhi College of Engineering and Research, Nagpur, India)

  • Latesh Malik

    (Department of Computer Science & Engineering, G. H. Raisoni College of Engineering, Nagpur, India)

Abstract

Genetic Algorithm (GA) mimics natural evolutionary process. Since dying of an organism is important part of natural evolutionary process, GA should have some mechanism for dying of solutions just like GA have crossover operator for birth of solutions. In nature, occurrence of event of dying of an organism has some reasons like aging, disease, malnutrition and so on. In this work we propose three strategies of dying or removal of solution from next generation population. Multi-objective Genetic Algorithm (MOGA) takes decision of removal of solution, based on one of these three strategies. Experiments were performed to show impact of dying of solutions and dying strategies on the performance of MOGA.

Suggested Citation

  • Rahila Patel & M. M. Raghuwanshi & Latesh Malik, 2014. "Multi-Objective Genetic Algorithm with Strategies for Dying of Solution," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 5(1), pages 69-85, January.
    • Handle: RePEc:igg:jaec00:v:5:y:2014:i:1:p:69-85
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