학술논문
Multi-Objective Optimization Using Kriging Model and Data Mining
Document Type
Academic Journal
Author
Source
International Journal of Aeronautical and Space Sciences. 2006-05 7(1):1-12
Subject
Language
Korean
ISSN
2093-274X
2093-2480
2093-2480
Abstract
In this study, a surrogate model is applied to multi-objective aerodynamic optimization design. For the balanced exploration and exploitation, each objective function is converted into the Expected Improvement (EI) and this value is used as fitness value in the multi-objective optimization instead of the objective function itself. Among the non-dominated solutions about EIs, additional sample points for the update of the Kriging model are selected. The present method was applied to a transonic airfoil design. Design results showed the validity of the present method. In order to obtain the information about design space, two data mining techniques are applied to design results: Analysis of Variance (ANOVA) and the Self-Organizing Map (SOM).