<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Most of the existing chaotic particle swarm optimization algorithms use logistic chaotic mapping. However, the chaotic sequence which is generated by the logistic chaotic mapping is not uniform enough. As a solution to this defect, this paper introduces the Anderson chaotic mapping to the chaotic particle swarm optimization, using it to initialize the position and velocity of the particle swarm. It self-adaptively controls the portion of particles to undergo chaos update through a change of the fitness variance. The numerical simulation results show that the convergence and global searching capability of the modified algorithm have been improved with the introduction of this mapping and it can efficiently avoid premature convergence.</p></abstract>

Most of the existing chaotic particle swarm optimization algorithms use logistic chaotic mapping. However, the chaotic sequence which is generated by the logistic chaotic mapping is not uniform enough. As a solution to this defect, this paper introduces the Anderson chaotic mapping to the chaotic particle swarm optimization, using it to initialize the position and velocity of the particle swarm. It self-adaptively controls the portion of particles to undergo chaos update through a change of the fitness variance. The numerical simulation results show that the convergence and global searching capability of the modified algorithm have been improved with the introduction of this mapping and it can efficiently avoid premature convergence.

Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation

School of Information and Mathematics of Yangtze University, Hubei Jingzhou, 434023 China; Institute of Petroleum Engineering Technology, Zhongyuan Bureau of Petroleum Exploration, Puyang Henan,457001 China

Mechanical Postdoctoral Station, Wuhan University of Technology, Wuhan Hubei, 430070 China

Key Laboratory of Exploration Technologies for Oil and Gas Resources, Ministry of Education, Yangtze University, Hubei Wuhan, 430100 China

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation"}

Most of the existing chaotic particle swarm optimization algorithms use logistic chaotic mapping. However, the chaotic sequence which is generated by the...

Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 70 - 80

DOI: https://doi.org/10.1515/cait-2015-0068

Schlüsselwörter
Chaos, particle swarm optimization, fitness variance, convergence rate

© 2015 Dong Yong et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 70 - 80

DOI: https://doi.org/10.1515/cait-2015-0068

SchlüsselwörterChaos, particle swarm optimization, fitness variance, convergence rate

© 2015 Dong Yong et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Chaos, particle swarm optimization, fitness variance, convergence rate