Volume 7 Number 5 (May. 2012)
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JSW 2012 Vol.7(5): 1030-1037 ISSN: 1796-217X
doi: 10.4304/jsw.7.5.1030-1037

Chaotic Hybrid Bacterial Colony Chemotaxis Algorithm Based on Tent Map

Jia-Ze Sun1, 2, Guo-Hua Geng1, Shu-Yan Wang2, and Ming-Quan Zhou3
1Institute of Visualization Technology, Northwest University, Xi ’an, China
2School of Computer Science & Technology, Xi ’an University of Post & Telecommunications Xi ’an, China
3School of Information Science and Technology, Beijing Normal University, Beijing, China

Abstract—Aiming at improving the global convergence speed of bacterial colony chemotaxis (BCC) optimization algorithm, a new chaotic hybrid bacterial colony chemotaxis (CHBCC) algorithm is introduced through the technique of hybrid algorithm. By integrating elitist strategy and chaotic optimization into bacterial colony chemotaxis optimization algorithm, it greatly enhances the local searching efficiency and global searching performance. Furthermore, the bacteria are divided into two sub-swarms and perform different operations to co-evolve, one sub-swarm searches via BCC and the other searches via chaos algorithm based on Tent Map at the same time. Simulation results on some benchmark functions show that CHBCC is pretty efficient to solve complex problems. It has high optimization efficiency, good global performance, and stable optimization outcomes. The performance of CHBCC is evidently better than BCC and BC.

Index Terms—bacterial colony chemotaxis, elitist strategy, chaotic optimization, Tent Map


Cite: Jia-Ze Sun, Guo-Hua Geng, Shu-Yan Wang, and Ming-Quan Zhou, "Chaotic Hybrid Bacterial Colony Chemotaxis Algorithm Based on Tent Map," Journal of Software vol. 7, no. 5, pp. 1030-1037, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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