BOOSTERS: A DERIVATIVE-FREE ALGORITHM BASED ON RADIAL BASIS FUNCTIONS

Derivative-free optimization (DFO) involves the methods used to minimize an expensive objective function when its derivatives are not available. We present here a trust-region algorithm based on Radial Basis Functions (RBFs). The main originality of our approach is the use of RBFs to build the trust...

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Bibliographic Details
Published inInternational journal of modelling & simulation Vol. 29; no. 1
Main Authors Oeuvray, R, Bierlaire, M
Format Journal Article
LanguageEnglish
Published 2009
Subjects
Algorithms
Boosters
Construction
Derivatives
Interpolation
Mathematical models
Optimization
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Summary:Derivative-free optimization (DFO) involves the methods used to minimize an expensive objective function when its derivatives are not available. We present here a trust-region algorithm based on Radial Basis Functions (RBFs). The main originality of our approach is the use of RBFs to build the trust-region models and our management of the interpolation points based on Newton fundamental polynomials. Moreover the complexity of our method is very attractive. We have tested the algorithm against the best state-of-the-art methods (UOBYQA, NEWUOA, DFO). The tests on the problems from the CUTEr collection show that BOOSTERS is performing very well on medium-size problems. Moreover, it is able to solve problems of dimension 200, which is considered very large in DFO.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:1925-7082
0228-6203
DOI:10.2316/Journal.205.2009.1.205-4634