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From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms
Xin-She Yang1; Suash Deb2; Simon Fong3; Xingshi He4; Yu-Xin Zhao5
2016-09-07
Source PublicationComputer
ISSN0018-9162
Volume49Issue:9Pages:52-59
Other Abstract

Nature has provided rich models for computational problem solving, including optimizations based on the swarm intelligence exhibited by fireflies, bats, and ants. These models can stimulate computer scientists to think nontraditionally in creating tools to address application design challenges.

DOI10.1109/MC.2016.292
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS IDWOS:000384132600008
PublisherIEEE COMPUTER SOC, 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1314 USA
The Source to ArticleEngineering Village
Scopus ID2-s2.0-84987654883
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Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorXin-She Yang
Affiliation1.Middlesex University
2.IT and Educational Consultant
3.University of Macau
4.Xi'An Polytechnic University
5.Harbin Engineering University
Recommended Citation
GB/T 7714
Xin-She Yang,Suash Deb,Simon Fong,et al. From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms[J]. Computer, 2016, 49(9), 52-59.
APA Xin-She Yang., Suash Deb., Simon Fong., Xingshi He., & Yu-Xin Zhao (2016). From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms. Computer, 49(9), 52-59.
MLA Xin-She Yang,et al."From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms".Computer 49.9(2016):52-59.
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