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High-dimensional derivative-free optimization via trust region surrogates in linear subspaces
OA Location
Author(s)
van de Berg, Damien
Shah, Nilay
del Rio-Chanona, Antonio
Type
Chapter
Abstract
Maintaining the benefits of derivative-free optimization in higher-dimensional decision spaces presents challenges for existing optimization methods. We introduce CUATRO_PLS - an extension of the CUATRO quadratic trust region optimizer that leverages intrinsic structures across high-dimensional black-box variables. CUATRO_PLS shows competitive convergence with leading derivative-free optimization algorithms in three high-dimensional chemical engineering case studies even in the absence or underestimation of known intrinsic dimensionality and is significantly faster than other model-based derivative-free optimization algorithms.
Date Issued
2024-06-26
Citation
Computer Aided Chemical Engineering, 2024, pp.3193-3198
URI
URL
DOI
ISBN
9780443288241
Publisher
Elsevier
Start Page
3193
End Page
3198
Journal / Book Title
Computer Aided Chemical Engineering
Volume
53
Copyright Statement
Copyright © 2024 Elsevier B.V. All rights are reserved.
Subjects
0904 Chemical Engineering
0907 Environmental Engineering
0914 Resources Engineering and Extractive Metallurgy
Chemical Engineering
Publication Status
Published
Date Publish Online
2024-06-26