用于多峰函数优化的免疫粒子群网络算法

Abstract

Abstract: Referred to the character of particle swarm optimization and immune network theory,an immune particle swarm network algorithm for multimodal function optimization is proposed.By making use of the information sharing and memory function of particle swarm,the cognitive part based on its own experience has been enhanced to improve local searching ability of the algorithm.The strategy of dynamic network suppression has been used to maintain diversity of population,and adjust adaptively the scale of particle swarm.Simulation results of typical test functions show the algorithm can not only improve population diversity effectively,but realize the combination of global optimization and local optimization well,thus has excellent optimization performance.

CLC Number:

TP18

XUE Wen-tao, WU Xiao-bei, XU Zhi-liang. Immune particle swarm network algorithm for multimodal function optimization[J]. Journal of Systems Engineering and Electronics, 2009, 31(3): 705-709.

References

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Immune particle swarm network algorithm for multimodal function optimization

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