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A sigmoid attractiveness based improved firefly algorithm and its applications in IIR filter design
Liu, Ao1,2,3; Li, Peng4; Deng, Xudong1,2; Ren, Liang1,2
2020-03-20
Source PublicationCONNECTION SCIENCE
ISSN0954-0091
Pages25
AbstractRecently, a novel population-based optimisation algorithm, namely firefly algorithm (FA), which mimics the flashing and attraction behaviour of fireflies, has shown promising performance in solving global optimisation problems. However, the preliminary studies have shown that FA often gets stuck in local optima. In this paper, we investigate the reasons why the FA suffers from getting stuck in local optima; and then propose an improved firefly algorithm (IFA). These improvements are twofold: first, a sigmoid-based attractiveness is employed to reformulate its definition and strengthen its local refinement ability; second, a dynamic step parameter tuning strategy is designed to adjust the random search intensity and narrow the search space iteratively to strengthen its global search ability. The empirical results indicate IFA can well balance between the global exploration and the local exploitation, and provides the best solutions, at least the competitive results, for most of 12 global optimisation problems over other FA variants. Besides, by employing IFA to solve well-known infinite impulse response filter design problems, we evaluate the effectiveness and efficiency of IFA. The experimental results and comparisons show that IFA performs better than, at least as competent again, other meta-heuristics in terms of the solution accuracy, solution robustness, and convergence rate.
KeywordFirefly algorithm evolutionary algorithms function optimisation IIR filter design
DOI10.1080/09540091.2020.1742660
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[71701156] ; Natural Science Foundation of Hubei Province of China[2017CFB427] ; Open Fund of Hubei Province Key Laboratory of Systems Science in Metallurgical Process, Wuhan University of Science and Technology[Y201901]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000524086900001
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/51014
Collection中国科学院数学与系统科学研究院
Corresponding AuthorLiu, Ao
Affiliation1.Wuhan Univ Sci & Technol, Evergrande Sch Management, Wuhan 430065, Peoples R China
2.Wuhan Univ Sci & Technol, Ctr Serv Sci & Engn, Wuhan 430065, Peoples R China
3.Wuhan Univ Sci & Technol, Hubei Prov Key Lab Syst Sci Met Proc, Wuhan 430065, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Liu, Ao,Li, Peng,Deng, Xudong,et al. A sigmoid attractiveness based improved firefly algorithm and its applications in IIR filter design[J]. CONNECTION SCIENCE,2020:25.
APA Liu, Ao,Li, Peng,Deng, Xudong,&Ren, Liang.(2020).A sigmoid attractiveness based improved firefly algorithm and its applications in IIR filter design.CONNECTION SCIENCE,25.
MLA Liu, Ao,et al."A sigmoid attractiveness based improved firefly algorithm and its applications in IIR filter design".CONNECTION SCIENCE (2020):25.
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