Abstract
Memetic Algorithm is a metaheuristic search method. It is based on both the natural evolution and individual learning by transmitting unit of information among them. In the present paper, Genetic Algorithm due to its good exploration capability is used for exploration and Particle Swarm Optimization (PSO) does local search. The memetic process is realized using the fitness information from the individual having best fitness value and searching around it locally with PSO. The proposed algorithm (PSO based memetic algorithm -pMA) is tested on 13 standard benchmark functions having unimodal and multimodal property. When results are compared, the proposed memetic algorithm shows better performance than GA and PSO. The performance of the discussed memetic algorithm is better in terms of convergence speed and quality of solutions.
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Devi, S., Jadhav, D.G., Pattnaik, S.S. (2011). PSO Based Memetic Algorithm for Unimodal and Multimodal Function Optimization. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_16
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DOI: https://doi.org/10.1007/978-3-642-27172-4_16
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