Abstract
This work focuses on multi-objective evolutionary optimization by approximation function. It uses the new general concept of evolution control to on-line enriching the database of correct solutions, which are the basis of the learning procedure for the kriging approximators. Substantially, given an initial very poor model approximation (small size of the database), the database, and consequently the models, is enriched by evaluating part of the individuals of the optimization process. The technique showed being efficient for the considered aerodynamic problem, by requiring few hundreds of true computations when the dimensionality of the problem is 5.
Original language | English |
---|---|
Title of host publication | 2005 IEEE Congress on Evolutionary Computation - Proceedings |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 1262-1267 |
Number of pages | 6 |
ISBN (Print) | 0780393635 |
DOIs | |
Publication status | Published - 12 Dec 2005 |
Event | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 - Edinburgh, Scotland, United Kingdom Duration: 2 Sept 2005 → 5 Sept 2005 |
Conference
Conference | 2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005 |
---|---|
Country/Territory | United Kingdom |
City | Edinburgh, Scotland |
Period | 2/09/05 → 5/09/05 |
Keywords
- optimization
- kriging approximation
- aerodynamics