DocumentCode
1791851
Title
Comparison between differential evolution and particle swarm optimization algorithms
Author
Dan Zhang ; Bin Wei
Author_Institution
Dept. of Automotive, Univ. of Ontario Inst. of Technol., Oshawa, ON, Canada
fYear
2014
fDate
3-6 Aug. 2014
Firstpage
239
Lastpage
244
Abstract
In this paper, the performance of differential evolution (DE) and particle swarm optimization (PSO) algorithms are compared and evaluated. The comparison is performed on eight benchmark functions f1-f8. New findings have been discovered for the PSO algorithm and the comparison results in this report show that DE generally is better than PSO in term of solution accuracy and robustness in almost all the problems. Generally, from the numerical results and graphic illustrations, we can demonstrate that DE is more efficient and robust compare to PSO, although PSO gives good results in some cases.
Keywords
algorithm theory; particle swarm optimisation; robust control; PSO algorithms; differential evolution; particle swarm optimization algorithms; robustness; Algorithm design and analysis; Benchmark testing; Optimization; Particle swarm optimization; Sociology; Statistics; differential evolution (DE); optimization algorithm; particle swarm optimization (PSO);
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location
Tianjin
Print_ISBN
978-1-4799-3978-7
Type
conf
DOI
10.1109/ICMA.2014.6885702
Filename
6885702
Link To Document