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dc.contributor.authorLee, IH-
dc.contributor.authorCha, JH-
dc.contributor.authorKim, JJ-
dc.contributor.authorPark, MW-
dc.date.accessioned2024-01-21T07:09:30Z-
dc.date.available2024-01-21T07:09:30Z-
dc.date.created2021-09-02-
dc.date.issued2004-05-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/137655-
dc.description.abstractThis paper proposes a representation for the embodiment design and a genetic algorithm suited for the representation. Since embodiment design consists of highly interrelated design processes, how to formalize and integrate the processes has become an important issue. In this paper, embodiment design is modeled as simultaneous multi-objective optimization of parametric designs for parts and of layout generation for structures. The study, thus, involves genotypes that are adequate to represent phenotypes of the models for the genetic algorithm to solve the given problems. We demonstrate the implementation of the genetic algorithm with the result applied to the gear equipment design.-
dc.languageEnglish-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleSynthesis of mechanical structures using a genetic algorithm-
dc.typeArticle-
dc.description.journalClass1-
dc.identifier.bibliographicCitationCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2004, PT 2, v.3044, pp.573 - 582-
dc.citation.titleCOMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2004, PT 2-
dc.citation.volume3044-
dc.citation.startPage573-
dc.citation.endPage582-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.identifier.wosid000222050600061-
dc.identifier.scopusid2-s2.0-35048901969-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalResearchAreaComputer Science-
dc.type.docTypeArticle; Proceedings Paper-
dc.subject.keywordAuthorEmbodiment Design-
dc.subject.keywordAuthorDesign Optimization-
dc.subject.keywordAuthorGenetic Algorithm-
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KIST Article > 2004
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