DocumentCode :
3307002
Title :
A Novel Crossover Operator for Particle Swarm Algorithm
Author :
Xie, Jiahua ; Yang, Jie
Author_Institution :
Sch. of Comput. & Inf., Shanghai Second Polytech. Univ., Shanghai, China
fYear :
2010
fDate :
24-25 April 2010
Firstpage :
161
Lastpage :
164
Abstract :
This paper presents a novel particle swarm optimization (PSO) algorithm to enhance the performance of PSO. The proposed approach, called LPSO, employs a Laplace Crossover operator (LC) to generate good candidate solutions. In order to verify the performance of LPSO, we test it on six well-known benchmark functions. The simulation results show that LPSO achieves better results than standard PSO in all test cases.
Keywords :
Benchmark testing; Computational modeling; Computer interfaces; Computer vision; Convergence; Evolutionary computation; Genetic mutations; Machine vision; Man machine systems; Particle swarm optimization; crossover; evolutionary computation; optimization; particle swarm optimization (PSO);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location :
Kaifeng, China
Print_ISBN :
978-1-4244-6595-8
Electronic_ISBN :
978-1-4244-6596-5
Type :
conf
DOI :
10.1109/MVHI.2010.123
Filename :
5532690
Link To Document :
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