Rate the Article: A Comparative Study of Classical Evolutionary Programming and Bat Algorithm, IJSR, Call for Papers, Online Journal
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

Downloads: 109 | Views: 403

Research Paper | Computer Science & Engineering | Bangladesh | Volume 6 Issue 1, January 2017 | Rating: 6.7 / 10


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


Edition: Volume 6 Issue 1, January 2017,


Pages: 2370 - 2373



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