International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Bangladesh | Computer Science Engineering | Volume 6 Issue 1, January 2017 | Pages: 2370 - 2373


A Comparative Study of Classical Evolutionary Programming and Bat Algorithm

D. M. Anisuzzaman, Shifat Sharmin Shapla

Abstract: Evolutionary Programming is an algorithm which uses natural selection of the fittest. In Classical Evolutionary Programming (CEP) uses Gaussian mutation. CEP is better at search in a small local neighborhood. It offers the best results for the unimodal and multimodal functions with only a few local minima. On the other hand, Swarm Intelligence algorithm inspired by natural behavior. Swarm Intelligence algorithm is the collective behavior of decentralized self-organized system. In this paper, we conducted an experimental comparison between CEP and a Swarm Intelligence algorithm - BAT. The experimental data shows that CEP performs better than BAT algorithm.

Keywords: Classical Evolutionary Programming, Swarm Intelligence Algorithm, BAT algorithm, offspring, continuous optimization



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