Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence

Giannakoglou, KC

dc.contributor.author	Giannakoglou, KC	en
dc.date.accessioned	2014-03-01T01:17:41Z
dc.date.available	2014-03-01T01:17:41Z
dc.date.issued	2002	en
dc.identifier.issn	0376-0421	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/14624
dc.subject	Computational Intelligence	en
dc.subject	Computer Model	en
dc.subject	Design Method	en
dc.subject	Evolutionary Algorithm	en
dc.subject	Literature Survey	en
dc.subject	Search Algorithm	en
dc.subject	Stochastic Optimization	en
dc.subject.classification	Engineering, Aerospace	en
dc.subject.other	Approximation theory	en
dc.subject.other	Computational methods	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Mathematical models	en
dc.subject.other	Optimization	en
dc.subject.other	Program processors	en
dc.subject.other	Random processes	en
dc.subject.other	Sensitivity analysis	en
dc.subject.other	Computational intelligence	en
dc.subject.other	Stochastic optimization	en
dc.subject.other	Aerospace engineering	en
dc.title	Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0376-0421(01)00019-7	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0376-0421(01)00019-7	en
heal.language	English	en
heal.publicationDate	2002	en
heal.abstract	Optimization and inverse design methods based on stochastic and, in particular, evolutionary algorithms, are currently being used in aeronautics since they offer a useful tool to help solving current and future technological problems. Despite their advantages, all of the population-based search algorithms require excessive CPU time due to the excessive number of candidate solutions which need to be evaluated through costly computational models. This paper focuses on the reduction of this computing cost, so as to make stochastic optimization both efficient and effective. Emphasis is laid on techniques which rely on the construction and use of surrogate or approximation models which may substitute for the exact and costly evaluation tool. A literature survey of a number of relevant methods is followed by numerous indicative examples, which demonstrate the usefulness of these methods. (C) 2002 Elsevier Science Ltd. All rights reserved. (C) 2002 Elsevier Science Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Progress in Aerospace Sciences	en
dc.identifier.doi	10.1016/S0376-0421(01)00019-7	en
dc.identifier.isi	ISI:000174827600003	en
dc.identifier.volume	38	en
dc.identifier.issue	1	en
dc.identifier.spage	43	en
dc.identifier.epage	76	en