Abstract
This paper proposes an improved particle swarm optimization utilizing iterative chaotic map with infinite collapses (ICMIC) perturbations (ICMICPSO) for global optimization of multimodal functions. The chaotic perturbation generated by the ICMIC is incorporated into the particle's velocity updating rule to make the particles have a larger potential space to fly. With the coefficient of chaotic perturbation decaying, the dynamics of ICMICPSO algorithm is a chaotic dynamics first and then a steepest descent dynamics. The proposed ICMICPSO method as hybrid optimization is tested on several widely used multimodal functions. Numerical results are compared with that of some other chaotic PSO methods available in the usual literature. The performance studies demonstrate that the effectiveness and efficiency of the proposed ICMICPSO approach are comparably to or better than that of the other CPSO variants in this paper.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.