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Published in:
2010 | OriginalPaper | Chapter
Co-Evolutionary Cultural Based Particle Swarm Optimization Algorithm
Authors : Yang Sun, Lingbo Zhang, Xingsheng Gu
Published in: Life System Modeling and Intelligent Computing
Publisher: Springer Berlin Heidelberg
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Particle swarm optimization (PSO), cultural algorithm (CA) and co-evolutionary algorithm (CEA) are all research hotspots in the field of intelligent computing. In order to apply their advantages, a hybrid algorithm CECBPSO is proposed in this paper. In the hybridization, PSO is introduced into the framework of CA, and then a co-evolutionary mechanism between two cultural based PSO algorithms is established. In this way, useful experiences can be exchanged among the populations, and randomly reinitialized particles are introduced into the algorithm. Both of them can help the algorithm improving the efficiency and escape the local optima when the particles get premature. The performance is evaluated on five test functions. Simulation results show that the hybridizing of the three algorithms greatly improves the performance.