Complexity of linearized quadratic penalty for optimization with nonlinear equality constraints

In this paper we consider a nonconvex optimization problem with nonlinear equality constraints. We assume that both, the objective function and the functional constraints, are locally smooth. For solving this problem, we propose a linearized quadratic penalty method, i.e., we linearize the objective...

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Veröffentlicht in:	arXiv.org 2024-11
Hauptverfasser:	Lahcen El Bourkhissi, Necoara, Ion
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Convergence Linearization Mathematics - Optimization and Control Optimization Regularization
Online-Zugang:	Volltext
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