TY - GEN
T1 - Kriging surrogate model enhanced by coordinate transformation of design space based on eigenvalue decomposition
AU - Namura, Nobuo
AU - Shimoyama, Koji
AU - Obayashi, Shigeru
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015
PY - 2015
Y1 - 2015
N2 - The Kriging surrogate model, which is frequently employed to apply evolutionary computation to real-world problems, with coordinate transformation of design space is proposed to improve the approximation accuracy of objective functions with correlated design variables. Eigenvalue decomposition is used to extract significant trends in the objective function from its gradients and identify suitable coordinates. Comparing with the ordinary Kriging model, the proposed method shows higher accuracy in the approximation of twodimensional test functions and reduces the computational cost to achieve the global optimization. In the application to an airfoil design problem with spline curves as correlated design variables, the proposed method achieves better performances not only in the approximation accuracy but also the ability to explore the optimal solution.
AB - The Kriging surrogate model, which is frequently employed to apply evolutionary computation to real-world problems, with coordinate transformation of design space is proposed to improve the approximation accuracy of objective functions with correlated design variables. Eigenvalue decomposition is used to extract significant trends in the objective function from its gradients and identify suitable coordinates. Comparing with the ordinary Kriging model, the proposed method shows higher accuracy in the approximation of twodimensional test functions and reduces the computational cost to achieve the global optimization. In the application to an airfoil design problem with spline curves as correlated design variables, the proposed method achieves better performances not only in the approximation accuracy but also the ability to explore the optimal solution.
KW - Airfoil design
KW - Efficient global optimization
KW - Eigenvalue decomposition
KW - Kriging model
KW - Spline curve
UR - http://www.scopus.com/inward/record.url?scp=84925340860&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84925340860&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-15934-8_22
DO - 10.1007/978-3-319-15934-8_22
M3 - Conference contribution
AN - SCOPUS:84925340860
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 321
EP - 335
BT - Evolutionary Multi-Criterion Optimization - 8th International Conference, EMO 2015, Proceedings
A2 - Gaspar-Cunha, António
A2 - Antunes, Carlos Henggeler
A2 - Coello, Carlos A. Coello
PB - Springer Verlag
T2 - 8th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2015
Y2 - 29 March 2015 through 1 April 2015
ER -