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A parallel Bees Algorithm implementation on GPU

dc.citation.epage279en_US
dc.citation.issue3en_US
dc.citation.spage271en_US
dc.citation.volume60en_US
dc.citation.woscount2
dc.contributor.authorLuo, Guo-Hengen_US
dc.contributor.authorHuang, Sheng-Kaien_US
dc.contributor.authorChang, Yue-Shanen_US
dc.contributor.authorYuan, Shyan-Mingen_US
dc.contributor.department資訊科學與工程研究所zh_TW
dc.contributor.departmentInstitute of Computer Science and Engineeringen_US
dc.date.accessioned2014-12-08T15:35:56Z
dc.date.available2014-12-08T15:35:56Z
dc.date.issued2014-03-01en_US
dc.description.abstractBees Algorithm is a population-based method that is a computational bound algorithm whose inspired by the natural behavior of honey bees to finds a near-optimal solution for the search problem. Recently, many parallel swarm based algorithms have been developed for running on GPU (Graphic Processing Unit). Since nowadays developing a parallel Bee Algorithm running on the GPU becomes very important. In this paper, we extend the Bees Algorithm (CUBA (i.e. CUDA based Bees Algorithm)) in order to be run on the CUDA (Compute Unified Device Architecture). CUBA (CUDA based Bees Algorithm). We evaluate the performance of CUBA by conducting some experiments based on numerous famous optimization problems. Results show that CUBA significantly outperforms standard Bees Algorithm in numerous different optimization problems. (C) 2013 Elsevier B.V. All rights reserved.en_US
dc.identifier.doi10.1016/j.sysarc.2013.09.007en_US
dc.identifier.issn1383-7621en_US
dc.identifier.journalJOURNAL OF SYSTEMS ARCHITECTUREen_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.sysarc.2013.09.007en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/24309
dc.identifier.wosnumberWOS:000333856800004
dc.language.isoen_USen_US
dc.subjectBees Algorithmen_US
dc.subjectParallel Bees Algorithmen_US
dc.subjectSwarm intelligenceen_US
dc.subjectGPGPUen_US
dc.subjectCUDAen_US
dc.titleA parallel Bees Algorithm implementation on GPUen_US
dc.typeArticleen_US

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