Volume 8 Number 5 (May 2013)
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JCP 2013 Vol.8(5): 1303-1308 ISSN: 1796-203X
doi: 10.4304/jcp.8.5.1303-1308

A Fractal Evolutionary Particle Swarm Optimizer

Xiaohong Qiusup>1, Xiaohui Qiusup>2, and Fang Liaosup>3
1 Software School, Jiangxi University of Science and Technology, Nanchang, China
2 Institute of Higher Education, Jiangxi Agricultural University, Nanchang, Chin
3 Temasek Laboratories, National University of Singapore, Singapore


Abstract—A Fractal Evolutionary Particle Swarm Optimization (FEPSO) is proposed based on the classical particle swarm optimization (PSO) algorithm. FEPSO applies the fractal Brownian motion model used to describe the irregular movement characteristics to simulate the optimization process varying in unknown mode, and include the implied trends to go to the global optimum. This will help the individual to escape from searching optimum too randomly and precociously. Compared with the classical PSO algorithm, each particle contains a fractal evolutionary phase in FEPSO. In this phase, each particle simulates a fractal Brownian motion with an estimated Hurst parameter to search the optimal solution in each sub dimensional space, and update correspond sub location. The simulation experiments show that this algorithm has a robust global search ability for most standard composite test functions. Its optimization ability performs much better than most recently proposed improved algorithm based on PSO.

Index Terms—fractal, evolutionary algorithm, particle swarm optimization , fractal Brownian motion, optimization, global

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Cite: Xiaohong Qiu, Xiaohui Qiu, and Fang Liao, " A Fractal Evolutionary Particle Swarm Optimizer," Journal of Computers vol. 8, no. 5, pp. 1303-1308, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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