Weight minimization of trusses with genetic algorithm

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Özet

This study is concerned with encoding types such as value encoding and binary encoding for continuous and discrete optimization with a GA, which is coded in FORTRAN and considers stress and displacement constraints, in view of weight minimization of truss structures. Moreover, when continuous optimization is performed, the challenge of huge search space due to the effort of considering continuous set of design variables is overcame by a mechanism introduced as restricted range approach (RRA) in this study. In comparison with the literature, it is concluded that the program developed in this study can be effectively used in the weight minimization of truss structures. It is also came to the conclusion that value encoding overcomes the adverse effects of Hamming-cliff, and that value encoding requires less computer memory and time, never destroys the fit chromosome. (C) 2010 Elsevier B.V. All rights reserved.

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https://rdlopen.rawdatalibrary.net/r/gumushane/16395Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.asoc.2010.10.006Yayıncı resmi DOI adresi
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WoS
68
OpenAlex
94
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorDede, Tayfun
dc.contributor.authorBekiroglu, Serkan
dc.contributor.authorAyvaz, Yusuf
dc.date.accessioned2026-10-22T10:29:18.098665126Z
dc.date.available2026-10-22T10:29:18.098665126Z
dc.date.issued2011-03
dc.description.abstractThis study is concerned with encoding types such as value encoding and binary encoding for continuous and discrete optimization with a GA, which is coded in FORTRAN and considers stress and displacement constraints, in view of weight minimization of truss structures. Moreover, when continuous optimization is performed, the challenge of huge search space due to the effort of considering continuous set of design variables is overcame by a mechanism introduced as restricted range approach (RRA) in this study. In comparison with the literature, it is concluded that the program developed in this study can be effectively used in the weight minimization of truss structures. It is also came to the conclusion that value encoding overcomes the adverse effects of Hamming-cliff, and that value encoding requires less computer memory and time, never destroys the fit chromosome. (C) 2010 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.asoc.2010.10.006
dc.identifier.eissn1872-9681
dc.identifier.endpage2575
dc.identifier.issn1568-4946
dc.identifier.issue2
dc.identifier.startpage2565
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/16395
dc.identifier.volume11
dc.identifier.wosWOS:000286373200105
dc.language.isoen
dc.publisherELSEVIER
dc.relation.ispartofAPPLIED SOFT COMPUTING
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectGenetic algorithm
dc.subjectOptimization
dc.subjectTruss structure
dc.subjectValue encoding
dc.subjectRestricted range approach
dc.subject.classificationComputer Science, Artificial Intelligence
dc.subject.classificationComputer Science, Interdisciplinary Applications
dc.subject.classificationComputer Science
dc.subject.otherOPTIMAL-DESIGN
dc.subject.otherOPTIMIZATION
dc.subject.otherDISCRETE
dc.titleWeight minimization of trusses with genetic algorithm
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex94
rdl.citation.wos68
rdl.oa.statusclosed
rdl.scopus.quartileQ1
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)