DocumentCode
2341789
Title
Hybrid particle swarm optimization with simulated annealing
Author
Wang, Xi-huai ; Li, Jun-Jun
Author_Institution
Dept. of Electr. & Autom., Shanghai Maritime Univ., China
Volume
4
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
2402
Abstract
Particle swarm optimization is a recently invented intelligent optimizer with several highly desirable attributes. A hybrid particle swarm optimization is proposed. This method integrates the particle swarm optimization with simulated annealing. The method is applied to six test functions´ optimization and the simulation shows that the performance of this algorithm is better than that of the adaptive particle swarm optimization and the genetic chaos optimization.
Keywords
simulated annealing; function optimization; genetic chaos optimization; hybrid particle swarm optimization; simulated annealing; Automation; Birds; Chaos; Computational modeling; Evolutionary computation; Genetics; Machine learning algorithms; Optimization methods; Particle swarm optimization; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382205
Filename
1382205
Link To Document