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Continuum Structural Topology Design with Genetic Algorithms

dc.contributor.authorJakiela, Mark John.en_US
dc.contributor.authorChapman, Colinen_US
dc.contributor.authorDuda, Jamesen_US
dc.contributor.authorAdewuya, Adenikeen_US
dc.contributor.authorSaitou, Kazuhiroen_US
dc.date.accessioned2011-11-14T16:30:43Z
dc.date.available2011-11-14T16:30:43Z
dc.date.issued2000-05-31en_US
dc.identifier.citationJakiela, M.; Chapman, C.; Duda, J.; Adewuya, A.; Saitou, K. (2000). Continuum structural topology design with genetic algorithms." Computer Methods in Applied Mechanics and Engineering 186(2): 339-356. <http://hdl.handle.net/2027.42/87244>en_US
dc.identifier.issn0045-7825en_US
dc.identifier.issn1879-2138en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/87244
dc.description.abstractThe genetic algorithm (GA), an optimization technique based on the theory of natural selection, is applied to structural topology design problems. After reviewing the GA and previous research in structural topology optimization, we describe a binary material/void design representation that is encoded in GA chromosome data structures. This representation is intended to approximate a material continuum as opposed to discrete truss structures. Four examples, showing the broad utility of the approach and representation, are then presented. A fifth example suggests an alternate representation that allows continuously-variable material density. Concluding discussion suggests recommended uses of the technique and describes ongoing and possible future work.en_US
dc.publisherElsevieren_US
dc.titleContinuum Structural Topology Design with Genetic Algorithmsen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMechanical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Mechanical Engineeringen_US
dc.contributor.affiliationotherDepartment of Mechanical Engineering, Washington University in St. Louis, Campus Box 1185, Jolley 305, One Brookings Drive, St. Louis, MO 63130-4899, USA.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/87244/4/Saitou43.pdf
dc.identifier.doi10.1016/S0045-7825(99)00390-4en_US
dc.identifier.sourceComputer Methods in Applied Mechanics and Engineeringen_US
dc.owningcollnameMechanical Engineering, Department of


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