Chaotic System Design of Swarm Intelligent Optimization Algorithm
- 10.2991/iccmcee-15.2015.109How to use a DOI?
- swarm intelligence, hybrid particle swarm; algorithm; optimization design
As swarm intelligence algorithm has such problems as poor convergence performance, long search time, and low search efficiency and it is also easy to stagnate at locally optimal solution in the process to solve complex optimization problems, self-adaptation hybrid particle swarm optimization algorithm based on improvement of two-dimensional mapping henon is put forward, which provides the combination mechanism of chaotic mapping and particle swarm with benchmark standard test problem as test function to prove the effectiveness of algorithm. The aim is to elevate the performance of swarm intelligence and to increase its capacity to solve issues in complex optimization problems.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - D. Pan PY - 2015/11 DA - 2015/11 TI - Chaotic System Design of Swarm Intelligent Optimization Algorithm BT - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering PB - Atlantis Press SP - 600 EP - 607 SN - 2352-5401 UR - https://doi.org/10.2991/iccmcee-15.2015.109 DO - 10.2991/iccmcee-15.2015.109 ID - Pan2015/11 ER -