Structural optimization using evolutionary algorithms

Lagaros, ND; Papadrakakis, M; Kokossalakis, G

dc.contributor.author	Lagaros, ND	en
dc.contributor.author	Papadrakakis, M	en
dc.contributor.author	Kokossalakis, G	en
dc.date.accessioned	2014-03-01T01:18:22Z
dc.date.available	2014-03-01T01:18:22Z
dc.date.issued	2002	en
dc.identifier.issn	0045-7949	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14959
dc.subject	Evolution strategies	en
dc.subject	Genetic algorithms	en
dc.subject	Handling of constraints	en
dc.subject	Sequential quadratic programming	en
dc.subject	Structural optimization	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Civil	en
dc.subject.other	Computational methods	en
dc.subject.other	Constraint theory	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Quadratic programming	en
dc.subject.other	Evolution strategies	en
dc.subject.other	Structural optimization	en
dc.title	Structural optimization using evolutionary algorithms	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0045-7949(02)00027-5	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0045-7949(02)00027-5	en
heal.language	English	en
heal.publicationDate	2002	en
heal.abstract	The objective of this paper is to investigate the efficiency of various evolutionary algorithms (EA), such as genetic algorithms and evolution strategies, when applied to large-scale structural sizing optimization problems. Both type of algorithms imitate biological evolution in nature and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism. In this paper modified versions of the basic EA are implemented to improve the performance of the optimization procedure. The modified versions of both genetic algorithms and evolution strategies combined with a mathematical programming method to form hybrid methodologies are also tested and compared and proved particularly promising. The numerical tests presented demonstrate the computational advantages of the discussed methods, which become more pronounced in large-scale optimization problems. (C) 2002 Elsevier Science Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Computers and Structures	en
dc.identifier.doi	10.1016/S0045-7949(02)00027-5	en
dc.identifier.isi	ISI:000176087600004	en
dc.identifier.volume	80	en
dc.identifier.issue	7-8	en
dc.identifier.spage	571	en
dc.identifier.epage	589	en