期刊
SOFT COMPUTING
卷 21, 期 17, 页码 5091-5102出版社
SPRINGER
DOI: 10.1007/s00500-016-2104-3
关键词
Firefly algorithm (FA); Swarm intelligence; Adaptive control parameters; Self-adaptive FA; Global optimization
资金
- Priority Academic Program Development of Jiangsu Higher Education Institutions
- Humanity and Social Science Foundation of Ministry of Education of China [13YJCZH174]
- National Natural Science Foundation of China [61305150, 61261039, 61402294, 61572328]
- Major Fundamental Research Project in the Science and Technology Plan of Shenzhen [JCYJ20140 828163633977, JCYJ20140418181958501, JCYJ201 50630105452814]
- Open Research Fund of China-UK Visual Information Processing Lab, National Social Science Foundation of China [15CGL040]
- Foundation of State Key Laboratory of Software Engineering [SKLSE2014-10-04]
- Natural Science Foundation of Jiangxi Province [20142BAB217020, 20151BAB217007]
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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