ON THE USE OF SURROGATE EVALUATION MODELS IN MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS

Karakasis, M; Giannakoglou, K

dc.contributor.author	Karakasis, M	en
dc.contributor.author	Giannakoglou, K	en
dc.date.accessioned	2014-03-01T01:53:28Z
dc.date.available	2014-03-01T01:53:28Z
dc.date.issued	2004	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/27029
dc.relation.uri	http://velos0.ltt.mech.ntua.gr/research/pdfs/3_070.pdf	en
dc.subject	Evaluation Model	en
dc.subject	Multi Objective Evolutionary Algorithm	en
dc.subject	Multi Objective Optimization	en
dc.subject	Radial Basis Function Network	en
dc.subject	Self Organized Map	en
dc.subject	Multi Objective Optimization Problem	en
dc.title	ON THE USE OF SURROGATE EVALUATION MODELS IN MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS	en
heal.type	journalArticle	en
heal.publicationDate	2004	en
heal.abstract	The use of surrogate evaluation models has found widespread use in evolu- tionary optimization. Regardless of the model itself and the implementation scheme, ap- proximation models are used to replace exact but costly evaluations, leading thus to lower design computational cost. However, the gain in computational cost reduces consider- ably in Multi-Objective optimization problems, where the prediction capability of surrogate	en