Firefly algorithm with adaptive control parameters
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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.
KeywordsFirefly algorithm (FA) Swarm intelligence Adaptive control parameters Self-adaptive FA Global optimization
This work is supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions, the Humanity and Social Science Foundation of Ministry of Education of China (No. 13YJCZH174), the National Natural Science Foundation of China (Nos. 61305150, 61261039, 61402294, and 61572328), Major Fundamental Research Project in the Science and Technology Plan of Shenzhen under Grants (Nos. JCYJ20140 828163633977, JCYJ20140418181958501, and JCYJ201 50630105452814), Open Research Fund of China-UK Visual Information Processing Lab, National Social Science Foundation of China (No. 15CGL040), the Foundation of State Key Laboratory of Software Engineering (No. SKLSE2014-10-04), and the Natural Science Foundation of Jiangxi Province (Nos. 20142BAB217020 and 20151BAB217007).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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