A branch-and-bound algorithm with growing datasets for large-scale parameter estimation

The solution of nonconvex parameter estimation problems with deterministic global optimization methods is desirable but challenging, especially if large measurement datasets are considered. We propose to exploit the structure of this class of optimization problems to enable their solution with the s...

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Bibliographic Details

Published in:	European journal of operational research Vol. 316; no. 1; pp. 36 - 45
Main Authors:	Sass, Susanne, Mitsos, Alexander, Bongartz, Dominik, Bell, Ian H., Nikolov, Nikolay I., Tsoukalas, Angelos
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.07.2024
Subjects:	Global optimization Large scale optimization Nonlinear programming Regression Spatial branch and bound algorithm Large scale optimization Regression Global optimization Nonlinear programming Spatial branch and bound algorithm
ISSN:	0377-2217
Online Access:	Get full text
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