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Comparison of MDO methods with mathematical examples

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dc.contributor.authorYi, Sang-il-
dc.contributor.authorShin, Jung-kyu-
dc.contributor.authorPARK, GYUNG JIN-
dc.date.accessioned2021-06-23T18:40:50Z-
dc.date.available2021-06-23T18:40:50Z-
dc.date.issued2008-05-
dc.identifier.issn1615-147X-
dc.identifier.issn1615-1488-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/43072-
dc.description.abstractRecently, engineering systems are quite large and complicated. The design requirements are fairly complex and it is not easy to satisfy them by considering only one discipline. Therefore, a design methodology that can consider various disciplines is needed. Multidisciplinary design optimization (MDO) is an emerging optimization method that considers a design environment with multiple disciplines. Seven methods have been proposed for MDO. They are Multiple-discipline-feasible (MDF), Individual-discipline-feasible (IDF), All-at-once (AAO), Concurrent subspace optimization (CSSO), Collaborative optimization (CO), Bi-level integrated system synthesis (BLISS), and Multidisciplinary design optimization based on independent subspaces (MDOIS). Through several mathematical examples, the performances of the methods are evaluated and compared. Specific requirements are defined for comparison and new types of mathematical problems are defined based on the requirements. All the methods are coded and the performances of the methods are compared qualitatively and quantitatively. © 2007 Springer-Verlag.-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleComparison of MDO methods with mathematical examples-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/s00158-007-0150-2-
dc.identifier.scopusid2-s2.0-41049115175-
dc.identifier.wosid000254206600001-
dc.identifier.bibliographicCitationStructural and Multidisciplinary Optimization, v.35, no.5, pp 391 - 402-
dc.citation.titleStructural and Multidisciplinary Optimization-
dc.citation.volume35-
dc.citation.number5-
dc.citation.startPage391-
dc.citation.endPage402-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMechanics-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryMechanics-
dc.subject.keywordPlusMathematical models-
dc.subject.keywordPlusProblem solving-
dc.subject.keywordPlusRequirements engineering-
dc.subject.keywordPlusMultidisciplinary design optimization (MDO)-
dc.subject.keywordPlusMultiple-discipline-feasible (MDF)-
dc.subject.keywordPlusMultiobjective optimization-
dc.subject.keywordAuthorAAO-
dc.subject.keywordAuthorBLISS-
dc.subject.keywordAuthorCO-
dc.subject.keywordAuthorCSSO-
dc.subject.keywordAuthorIDF-
dc.subject.keywordAuthorMDF-
dc.subject.keywordAuthorMDOIS-
dc.subject.keywordAuthorMultidisciplinary design optimization (MDO)-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s00158-007-0150-2-
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