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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Bibliographic Details
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
Online Access:Get full text
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Summary: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.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-016-2104-3