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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Vydané v:	European journal of operational research Ročník 316; číslo 1; s. 36 - 45
Hlavní autori:	Sass, Susanne, Mitsos, Alexander, Bongartz, Dominik, Bell, Ian H., Nikolov, Nikolay I., Tsoukalas, Angelos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.07.2024
Predmet:	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
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