Comparison between differential evolution and particle swarm optimization algorithms

Dan Zhang; Bin Wei

doi:10.1109/ICMA.2014.6885702

Comparison between differential evolution and particle swarm optimization algorithms

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

24 Citations (Scopus)

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.

Original language	English
Title of host publication	2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
Publisher	IEEE Computer Society
Pages	239-244
Number of pages	6
ISBN (Print)	9781479939787
DOIs	https://doi.org/10.1109/ICMA.2014.6885702
Publication status	Published - 2014
Externally published	Yes
Event	11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014 - Tianjin, China Duration: 3 Aug 2014 → 6 Aug 2014

Publication series

Name	2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014

Conference

Conference	11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014
Country/Territory	China
City	Tianjin
Period	3/08/14 → 6/08/14

Keywords

Differential evolution (DE)
Optimization algorithm
Particle swarm optimization (PSO)

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering
Mechanical Engineering

More information

10.1109/ICMA.2014.6885702

Cite this

Zhang, D., & Wei, B. (2014). Comparison between differential evolution and particle swarm optimization algorithms. In 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014 (pp. 239-244). Article 68856702 (2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014). IEEE Computer Society. https://doi.org/10.1109/ICMA.2014.6885702

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title = "Comparison between differential evolution and particle swarm optimization algorithms",

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.",

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author = "Dan Zhang and Bin Wei",

year = "2014",

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language = "English",

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series = "2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014",

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Zhang, D & Wei, B 2014, Comparison between differential evolution and particle swarm optimization algorithms. in 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014., 68856702, 2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014, IEEE Computer Society, pp. 239-244, 11th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014, Tianjin, China, 3/08/14. https://doi.org/10.1109/ICMA.2014.6885702

Comparison between differential evolution and particle swarm optimization algorithms. / Zhang, Dan; Wei, Bin.
2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014. IEEE Computer Society, 2014. p. 239-244 68856702 (2014 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2014).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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Comparison between differential evolution and particle swarm optimization algorithms

Abstract

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Keywords

ASJC Scopus subject areas

More information

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