期刊
INFORMATION SCIENCES
卷 382, 期 -, 页码 374-387出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2016.12.024
关键词
Firefly algorithm (FA); Attraction; Neighborhood attraction; Random attraction; Optimization
资金
- Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
- Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET)
- National Natural Science Foundation of China [61663028, 61663029, 61261039]
- Natural Science Foundation of Shanxi Province [201601D011045]
- Science and Technology Plan Project of Jiangxi Provincial Education Department [KJLD13096, GJJ151115]
Firefly algorithm (FA) is a new optimization technique based on swarm intelligence. It simulates the social behavior of fireflies. The search pattern of FA is determined by the attractions among fireflies, whereby a less bright firefly moves toward a brighter firefly. In FA, each firefly can be attracted by all other brighter fireflies in the population. However, too many attractions may result in oscillations during the search process and high computational time complexity. To overcome these problems, we propose a new FA variant called FA with neighborhood attraction (NaFA). In NaFA, each firefly is attracted by other brighter fireflies selected from a predefined neighborhood rather than those from the entire population. Experiments are conducted using several well-known benchmark functions. The results show that the proposed strategy can efficiently improve the accuracy of solutions and reduce the computational time complexity. (C) 2016 Elsevier Inc. All rights reserved.
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