Immune particle swarm optimization based on sharing mechanism

Authors:
Chunxia Hu;Jianchao Zeng;Jing Jie
Affiliations:
Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan, China;Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan, China;Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan, China
Venue:
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Year:
2007

Citing 4
Cited 0

Swarm intelligence

Swarm intelligence
Recent approaches to global optimization problems through Particle Swarm Optimization

Natural Computing: an international journal
Parameter Selection in Particle Swarm Optimization

EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Comparison between Genetic Algorithms and Particle Swarm Optimization

EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII

Quantified Score

Hi-index	0.00

Visualization

Abstract

Sharing mechanism is introduced into particle swarm optimization. Fitness values of particles are updated to sharing fitness values. Particles with higher sharing fitness value are punished and particles with smaller sharing fitness value are remained as memory particles. Particles are updated with memory particles and clone selection when global best have not changed in some continuous generations. Population diversity is increased by this way. At the same time the particle with the best fitness value is saved. The modified algorithm can avoid the local optimization and has better search performance to multi-peak functions. The experimental results show the modified algorithm has better convergence performance than standard particle swarm optimization algorithm.