An Alternating Augmented Lagrangian method for constrained nonconvex optimization

We consider the problem of minimizing a smooth nonconvex function over a structured convex feasible set, that is, defined by two sets of constraints that are easy to treat when considered separately. In order to exploit the structure of the problem, we define an equivalent formulation by duplicating...

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Bibliographic Details

Published in:	Optimization methods & software Vol. 35; no. 3; pp. 502 - 520
Main Authors:	Galvan, G., Lapucci, M., Levato, T., Sciandrone, M.
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 03.05.2020 Taylor & Francis Ltd
Subjects:	Algorithms Alternating direction method of multipliers augmented Lagrangian Constraints Convexity decomposition Exact solutions global convergence Machine learning nonconvex objective function Nonlinear programming Optimization penalty method Queuing theory
ISSN:	1055-6788, 1029-4937
Online Access:	Get full text
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