Firefly algorithm with adaptive control parameters

Firefly algorithm (FA) is a new swarm intelligence optimization method, which has shown good search abilities on many optimization problems. However, the performance of FA highly depends on its control parameters. In this paper, we investigate the control parameters of FA, and propose a modified FA...

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Published in:	Soft computing (Berlin, Germany) Vol. 21; no. 17; pp. 5091 - 5102
Main Authors:	Wang, Hui, Zhou, Xinyu, Sun, Hui, Yu, Xiang, Zhao, Jia, Zhang, Hai, Cui, Laizhong
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2017 Springer Nature B.V
Subjects:	Adaptive algorithms Adaptive control Algorithms Artificial Intelligence Computational Intelligence Control Design optimization Engineering Heuristic methods Mathematical Logic and Foundations Mechatronics Methodologies and Application Optimization Parameter modification Robotics Swarm intelligence Adaptive control parameters Global optimization Firefly algorithm (FA) Swarm intelligence Self-adaptive FA
ISSN:	1432-7643, 1433-7479
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Abstract	Firefly algorithm (FA) is a new swarm intelligence optimization method, which has shown good search abilities on many optimization problems. However, the performance of FA highly depends on its control parameters. In this paper, we investigate the control parameters of FA, and propose a modified FA called FA with adaptive control parameters (ApFA). To verify the performance of ApFA, experiments are conducted on a set of well-known benchmark problems. Results show that the ApFA outperforms the standard FA and five other recently proposed FA variants.
AbstractList	Firefly algorithm (FA) is a new swarm intelligence optimization method, which has shown good search abilities on many optimization problems. However, the performance of FA highly depends on its control parameters. In this paper, we investigate the control parameters of FA, and propose a modified FA called FA with adaptive control parameters (ApFA). To verify the performance of ApFA, experiments are conducted on a set of well-known benchmark problems. Results show that the ApFA outperforms the standard FA and five other recently proposed FA variants.
Author	Cui, Laizhong Yu, Xiang Wang, Hui Sun, Hui Zhou, Xinyu Zhao, Jia Zhang, Hai
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Snippet	Firefly algorithm (FA) is a new swarm intelligence optimization method, which has shown good search abilities on many optimization problems. However, the...
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SubjectTerms	Adaptive algorithms Adaptive control Algorithms Artificial Intelligence Computational Intelligence Control Design optimization Engineering Heuristic methods Mathematical Logic and Foundations Mechatronics Methodologies and Application Optimization Parameter modification Robotics Swarm intelligence
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Title	Firefly algorithm with adaptive control parameters
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