DocumentCode :
3318592
Title :
An adaptive diversity strategy for particle swarm optimization
Author :
Wang, Fang ; Feng, Naiqin ; Qiu, Yuhui
Author_Institution :
Intelligent Software & Software Eng. Lab., Southwest Univ., Chongqing, China
fYear :
2005
fDate :
30 Oct.-1 Nov. 2005
Firstpage :
760
Lastpage :
764
Abstract :
In this paper, we present a diversity strategy for particle swarm optimizer. The modified algorithm re-initializes part of particles with poorer fitness during the searching process. It is empirically tested and compared with other published methods on many famous benchmark functions. The experimental results illustrate that the proposed algorithm has the potential to achieve higher success ratio and better solution quality. It is very competitive for hard multimodal function optimization.
Keywords :
particle swarm optimisation; search problems; adaptive diversity strategy; particle swarm optimization; Benchmark testing; Birds; Convergence; Genetic algorithms; Genetic engineering; Laboratories; Optimization methods; Particle swarm optimization; Software engineering; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on
Print_ISBN :
0-7803-9361-9
Type :
conf
DOI :
10.1109/NLPKE.2005.1598838
Filename :
1598838
Link To Document :
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