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Journal of Emerging Trends in Computing and Information Sciences >> Call for Papers Vol. 8 No. 3, March 2017

Journal of Emerging Trends in Computing and Information Sciences

Comparative Assessment of Genetic and Memetic Algorithms

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Author H. A. Sanusi, A. Zubair , R. O. Oladele
ISSN 2079-8407
On Pages 498-508
Volume No. 2
Issue No. 10
Issue Date October 01, 2011
Publishing Date October 01, 2011
Keywords Optimization, Accuracy, Convergence, Evolutionary Algorithm, Iteration


Abstract

This work investigates the performance of two Evolutionary Algorithms Genetic Algorithm and Memetic Algorithm for Constrained Optimization Problem. In particular, a knapsack problem was solved using the two algorithms and their results were compared. Two selection techniques were used for both algorithms. The results of comparative analysis show that Roulette-Wheel selection method outperforms Ranking and scaling method by 4.1% in term of the accuracy of the optimal results obtained. Furthermore, Memetic Algorithm converges faster than Genetic Algorithm even as it also produces more optimal results than Genetic Algorithm produces by a factor of 4.9% when the results obtained from Roulette Wheel selection were compared for both algorithms. It is however pertinent to state that the time taken by an iteration in Genetic Algorithm is 35.9% less than the time taken by an iteration in Memetic Algorithm.  

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