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Multi-Objective Genetic Algorithm with Strategies for Dying of Solution

Multi-Objective Genetic Algorithm with Strategies for Dying of Solution

Rahila Patel, M. M. Raghuwanshi, Latesh Malik
Copyright: © 2014 |Volume: 5 |Issue: 1 |Pages: 17
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466652392|DOI: 10.4018/ijaec.2014010105
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MLA

Patel, Rahila, et al. "Multi-Objective Genetic Algorithm with Strategies for Dying of Solution." IJAEC vol.5, no.1 2014: pp.69-85. http://doi.org/10.4018/ijaec.2014010105

APA

Patel, R., Raghuwanshi, M. M., & Malik, L. (2014). Multi-Objective Genetic Algorithm with Strategies for Dying of Solution. International Journal of Applied Evolutionary Computation (IJAEC), 5(1), 69-85. http://doi.org/10.4018/ijaec.2014010105

Chicago

Patel, Rahila, M. M. Raghuwanshi, and Latesh Malik. "Multi-Objective Genetic Algorithm with Strategies for Dying of Solution," International Journal of Applied Evolutionary Computation (IJAEC) 5, no.1: 69-85. http://doi.org/10.4018/ijaec.2014010105

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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.

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