Tuesday, 15:15 - 15:40 h, Room: H 2053

 

Laurent Dumas
A new global optimization method based on a sparse grid metamodel

Coauthors: Frederic Delbos, Eugenio Echague

 

Abstract:
A new global optimization method is presented here aimed at solving a general black-box optimization problem where function evaluations are expensive. Our work is motivated by many problems in the oil industry, coming from several domains like reservoir engineering, molecular modeling, engine calibration and inverse problems in geosciences. Even if evolutionary algorithms are often a good tool to solve these problems, they sometimes need too many function evaluations, especially in high-dimension cases. To overcome this difficulty, we propose here a new approach, called SGOM, using the Sparse Grid interpolation method with a refinement process as metamodel.

 

Talk 1 of the invited session Tue.3.H 2053
"From quadratic through factorable to black-box global optimization" [...]
Cluster 9
"Global optimization" [...]

 

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