A Novel Hybrid Firefly Algorithm for Global Optimization
Publication Date
September 29, 2016
Journal
PLOS ONE
Authors
Lina Zhang, Liqiang Liu, Xin She Yang & Yuntao Dai
Volume
11
Issue
9
Pages
e0163230
DOI
https://dx.plos.org/10.1371/journal.pone.0163230
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0163230
Web of Science
000384328500030
Scopus
84991721416
Mendeley
http://www.mendeley.com/research/novel-hybrid-firefly-algorithm-global-optimization-1
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Mendeley | Further Information

{"title"=>"A Novel Hybrid Firefly Algorithm for Global Optimization", "type"=>"journal", "authors"=>[{"first_name"=>"Lina", "last_name"=>"Zhang"}, {"first_name"=>"Liqiang", "last_name"=>"Liu"}, {"first_name"=>"Xin-She", "last_name"=>"Yang"}, {"first_name"=>"Yuntao", "last_name"=>"Dai"}], "year"=>2016, "source"=>"PLOS ONE", "identifiers"=>{"isbn"=>"1932-6203 (Electronic)\r1932-6203 (Linking)", "issn"=>"1932-6203", "doi"=>"10.1371/journal.pone.0163230", "pmid"=>"27685869"}, "id"=>"93023706-0c69-3d95-8825-aaa07fc7a7c0", "abstract"=>"Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate.", "link"=>"http://www.mendeley.com/research/novel-hybrid-firefly-algorithm-global-optimization-1", "reader_count"=>18, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>3, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Researcher"=>3, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>3, "Student > Bachelor"=>2, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>3, "Mathematics"=>1, "Computer Science"=>10, "Neuroscience"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Neuroscience"=>{"Neuroscience"=>1}, "Computer Science"=>{"Computer Science"=>10}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}}, "group_count"=>0}

Scopus | Further Information

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