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From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms
Yang, Xin-She1; Deb, Suash2; Fong, Simon3; He, Xingshi4; Zhao, Yu-Xin5
2016-09-01
Source PublicationComputer
ISSN00189162
Volume49Issue:9Pages:52-59
AbstractNature 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. © 2016 IEEE.
DOI10.1109/MC.2016.292
Language英语
The Source to ArticleEngineering Village
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Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Middlesex University, United Kingdom;
2.IT and Educational Consultant, United Kingdom;
3.University of Macau, China;
4.Xi'An Polytechnic University, China;
5.Harbin Engineering University, China
Recommended Citation
GB/T 7714
Yang, Xin-She,Deb, Suash,Fong, Simon,et al. From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms[J]. Computer,2016,49(9):52-59.
APA Yang, Xin-She,Deb, Suash,Fong, Simon,He, Xingshi,&Zhao, Yu-Xin.(2016).From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms.Computer,49(9),52-59.
MLA Yang, Xin-She,et al."From Swarm Intelligence to Metaheuristics: Nature-Inspired Optimization Algorithms".Computer 49.9(2016):52-59.
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