An Optimal Interpolation Set for Model-Based Derivative-Free Optimization Methods

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Hauptverfasser: Ragonneau, Tom M., Zhang, Zaikun
Format: Preprint
Veröffentlicht: 2023
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author Ragonneau, Tom M.
Zhang, Zaikun
author_facet Ragonneau, Tom M.
Zhang, Zaikun
contents This paper demonstrates the optimality of an interpolation set employed in derivative-free trust-region methods. This set is optimal in the sense that it minimizes the constant of well-poisedness in a ball centred at the starting point. It is chosen as the default initial interpolation set by many derivative-free trust-region methods based on underdetermined quadratic interpolation, including NEWUOA, BOBYQA, LINCOA, and COBYQA. Our analysis provides a theoretical justification for this choice.
format Preprint
id arxiv_https___arxiv_org_abs_2302_09992
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle An Optimal Interpolation Set for Model-Based Derivative-Free Optimization Methods
Ragonneau, Tom M.
Zhang, Zaikun
Optimization and Control
90C56, 41A10, 65K05, 90C30
This paper demonstrates the optimality of an interpolation set employed in derivative-free trust-region methods. This set is optimal in the sense that it minimizes the constant of well-poisedness in a ball centred at the starting point. It is chosen as the default initial interpolation set by many derivative-free trust-region methods based on underdetermined quadratic interpolation, including NEWUOA, BOBYQA, LINCOA, and COBYQA. Our analysis provides a theoretical justification for this choice.
title An Optimal Interpolation Set for Model-Based Derivative-Free Optimization Methods
topic Optimization and Control
90C56, 41A10, 65K05, 90C30
url https://arxiv.org/abs/2302.09992