On the numerical performance of finite-difference-based methods for derivative-free optimization-Reference-Cited by-同舟云学术

On the numerical performance of finite-difference-based methods for derivative-free optimization

Published:2022-09-26 Issue:2 Volume:38 Page:289-311
ISSN:1055-6788
Container-title:Optimization Methods and Software
language:en
Short-container-title:Optimization Methods and Software

Author:

Shi Hao-Jun Michael¹,Qiming Xuan Melody¹,Oztoprak Figen²,Nocedal Jorge¹

Affiliation:

1. Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA

2. Artelys Corporation, Paris, France

Funder

Office of Naval Research

National Science Foundation

Publisher

Informa UK Limited

Subject

Applied Mathematics,Control and Optimization,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/10556788.2022.2121832

Reference50 articles.

1. Derivative-Free and Blackbox Optimization

2. Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization

3. Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods

4. A.S. Berahas, L. Cao, K. Choromanski and K. Scheinberg, Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization, preprint (2019). Available at arXiv:1905.13043.

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