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Swarm intelligence: past, present and future
Yang X.-S.3; Deb S.1; Zhao Y.-X.4; Fong S.2; He X.6
2018-09-01
Source PublicationSoft Computing
ISSN14337479 14327643
Volume22Issue:18Pages:5923-5933
AbstractMany optimization problems in science and engineering are challenging to solve, and the current trend is to use swarm intelligence (SI) and SI-based algorithms to tackle such challenging problems. Some significant developments have been made in recent years, though there are still many open problems in this area. This paper provides a short but timely analysis about SI-based algorithms and their links with self-organization. Different characteristics and properties are analyzed here from both mathematical and qualitative perspectives. Future research directions are outlined, and open questions are also highlighted.
KeywordBioinspired computing Metaheuristics Nature-inspired algorithms Optimization Self-organization Swarm intelligence
DOI10.1007/s00500-017-2810-5
URLView the original
Language英語
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Cited Times [WOS]:23   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.IT & Educational Consultant
2.Universidade de Macau
3.Middlesex University
4.Harbin Engineering University
5.Victoria University Melbourne
6.Xi’an Polytechnic University
Recommended Citation
GB/T 7714
Yang X.-S.,Deb S.,Zhao Y.-X.,et al. Swarm intelligence: past, present and future[J]. Soft Computing,2018,22(18):5923-5933.
APA Yang X.-S.,Deb S.,Zhao Y.-X.,Fong S.,&He X..(2018).Swarm intelligence: past, present and future.Soft Computing,22(18),5923-5933.
MLA Yang X.-S.,et al."Swarm intelligence: past, present and future".Soft Computing 22.18(2018):5923-5933.
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