Zobrazit minimální záznam

dc.contributor.authorZhao, Fengqiang
dc.contributor.authorLi, Guangqiang
dc.contributor.authorYang, Chao
dc.contributor.authorAbraham, Ajith
dc.contributor.authorLiu, Hongbo
dc.date.accessioned2014-08-26T13:23:59Z
dc.date.available2014-08-26T13:23:59Z
dc.date.issued2014
dc.identifier.citationNeurocomputing. 2014, vol. 132, p. 68-78.cs
dc.identifier.issn0925-2312
dc.identifier.issn1872-8286
dc.identifier.urihttp://hdl.handle.net/10084/105776
dc.description.abstractPacking and layout problems have wide applications in engineering practice. However, they belong to NP (non-deterministic polynomial)-complete problems. In this paper, we introduce human intelligence into the computational intelligent algorithms, namely particle swarm optimization (PSO) and immune algorithms (IA). A novel human–computer cooperative PSO-based immune algorithm (HCPSO-IA) is proposed, in which the initial population consists of the initial artificial individuals supplied by human and the initial algorithm individuals are generated by a chaotic strategy. Some new artificial individuals are introduced to replace the inferior individuals of the population. HCPSO-IA benefits by giving free rein to the talents of designers and computers, and contributes to solving complex layout design problems. The experimental results illustrate that the proposed algorithm is feasible and effective.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesNeurocomputingcs
dc.relation.urihttp://dx.doi.org/10.1016/j.neucom.2013.03.062cs
dc.rightsCopyright © 2013 Elsevier B.V. All rights reserved.cs
dc.subjecthuman–computer cooperationcs
dc.subjectgenetic algorithmscs
dc.subjectimmune functioncs
dc.subjectparticle swarm optimizationcs
dc.subjecthybridcs
dc.subjectlayoutcs
dc.titleA human-computer cooperative particle swarm optimization based immune algorithm for layout designcs
dc.typearticlecs
dc.identifier.doi10.1016/j.neucom.2013.03.062
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume132cs
dc.description.lastpage78cs
dc.description.firstpage68cs
dc.identifier.wos000334480500007


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