forgot password?
register here
Research articles
  search articles
  reviews guidelines
  articles index
My Pages
my alerts
  my messages
  my reviews
  my favorites
Members: 3652
Articles: 2'545'386
Articles rated: 2609

24 June 2024
  » arxiv » 2302.00363

 Article overview

Implicit augmented Lagrangian and generalized optimization
Alberto De Marchi ;
Date 1 Feb 2023
AbstractGeneralized nonlinear programming is considered in the fully nonconvex setting, capturing a variety of problems that include nonsmooth objectives, combinatorial structures, and nonlinear, set-membership constraints. The augmented Lagrangian framework is extended to this broad problem class, preserving an implicit formulation and treating slack variables merely as a formal device. Based on parametric optimization and variational analysis notions, a tailored stationarity concept is devised to better qualify the iterates, generated as approximate solutions to a sequence of subproblems. Using this sharp characterization and a lifted reformulation, a suitable multiplier update rule is derived, while asymptotic properties and convergence guarantees are established for a safeguarded augmented Lagrangian scheme. A numerical example indicates the benefits of the advocated implicit approach.
Source arXiv, 2302.00363
Services Forum | Review | PDF | Favorites   
Visitor rating: did you like this article? no 1   2   3   4   5   yes

No review found.
 Did you like this article?

This article or document is ...
of broad interest:
Global appreciation:

  Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
» my Online CV
» Free

home  |  contact  |  terms of use  |  sitemap
Copyright © 2005-2024 - Scimetrica