Chaotic System Design of Swarm Intelligent Optimization Algorithm

DOI

10.2991/iccmcee-15.2015.109How to use a DOI?

Keywords

swarm intelligence, hybrid particle swarm; algorithm; optimization design

Abstract

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.

Copyright

© 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/).

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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  -