A New Optimizaiton Algorithm for Function Optimization

Authors:
Xuesong Yan;Qinghua Wu;Hanmin Liu
Affiliations:
School of Computer Science, Chin University of Geoscience, Wuhan, China 430074;Faculty of Computer Science and Engineering, WuHan Institute of Technology, Wuhan, China 430074;Wuhan Institute of Shipbuilding Technology, Wuhan, China 430050
Venue:
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Year:
2009

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Abstract

Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities. In order to get rid of the disadvantages of standard Particle Swarm Optimization algorithm like being trapped easily into a local optimum, this paper improves the standard PSO and proposes a new algorithm to solve these problems. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with standard PSO on the Benchmarks function, the new algorithm produces more efficient results.