Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization

A worst-case complexity bound is proved for a sequential quadratic optimization (commonly known as SQP) algorithm that has been designed for solving optimization problems involving a stochastic objective function and deterministic nonlinear equality constraints. Barring additional terms that arise d...

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Vydané v:	Mathematical programming Ročník 205; číslo 1-2; s. 431 - 483
Hlavní autori:	Curtis, Frank E., O’Neill, Michael J., Robinson, Daniel P.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2024 Springer
Predmet:	Algorithms Analysis Calculus of Variations and Optimal Control; Optimization Combinatorics Full Length Paper Management science Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Methods Numerical Analysis Theoretical 68Q25 68W40 65K05 Nonlinear optimization 90C06 Sequential quadratic optimization 65Y20 Worst-case complexity 90C30 90C55 49M37 Stochastic optimization 62L20
ISSN:	0025-5610, 1436-4646
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