A Comparative Study of Classical Evolutionary Programming and Bat Algorithm
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: 376

Research Paper | Computer Science & Engineering | Bangladesh | Volume 6 Issue 1, January 2017 | Popularity: 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


DOI: https://www.doi.org/10.21275/ART2017514


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D. M. Anisuzzaman, Shifat Sharmin Shapla, "A Comparative Study of Classical Evolutionary Programming and Bat Algorithm", International Journal of Science and Research (IJSR), Volume 6 Issue 1, January 2017, pp. 2370-2373, https://www.ijsr.net/getabstract.php?paperid=ART2017514, DOI: https://www.doi.org/10.21275/ART2017514

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