Continuum Structural Topology Design with Genetic Algorithms
dc.contributor.author | Jakiela, Mark John. | en_US |
dc.contributor.author | Chapman, Colin | en_US |
dc.contributor.author | Duda, James | en_US |
dc.contributor.author | Adewuya, Adenike | en_US |
dc.contributor.author | Saitou, Kazuhiro | en_US |
dc.date.accessioned | 2011-11-14T16:30:43Z | |
dc.date.available | 2011-11-14T16:30:43Z | |
dc.date.issued | 2000-05-31 | en_US |
dc.identifier.citation | Jakiela, 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.issn | 0045-7825 | en_US |
dc.identifier.issn | 1879-2138 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/87244 | |
dc.description.abstract | The 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.publisher | Elsevier | en_US |
dc.title | Continuum Structural Topology Design with Genetic Algorithms | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Mechanical Engineering | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Mechanical Engineering | en_US |
dc.contributor.affiliationother | Department 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.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/87244/4/Saitou43.pdf | |
dc.identifier.doi | 10.1016/S0045-7825(99)00390-4 | en_US |
dc.identifier.source | Computer Methods in Applied Mechanics and Engineering | en_US |
dc.owningcollname | Mechanical Engineering, Department of |
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