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