An Augmented Lagrangian Method for Cardinality-Constrained Optimization Problems

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Christian Kanzow - , Julius-Maximilians-Universität Würzburg (Autor:in)
  • Andreas Budi Raharja - , Julius-Maximilians-Universität Würzburg (Autor:in)
  • Alexandra Schwartz - , Professur für Mathematische Optimierung (Autor:in)

Abstract

A reformulation of cardinality-constrained optimization problems into continuous nonlinear optimization problems with an orthogonality-type constraint has gained some popularity during the last few years. Due to the special structure of the constraints, the reformulation violates many standard assumptions and therefore is often solved using specialized algorithms. In contrast to this, we investigate the viability of using a standard safeguarded multiplier penalty method without any problem-tailored modifications to solve the reformulated problem. We prove global convergence towards an (essentially strongly) stationary point under a suitable problem-tailored quasinormality constraint qualification. Numerical experiments illustrating the performance of the method in comparison to regularization-based approaches are provided.

Details

OriginalspracheEnglisch
Seiten (von - bis)793-813
Seitenumfang21
FachzeitschriftJournal of Optimization Theory and Applications
Jahrgang189
Ausgabenummer3
PublikationsstatusVeröffentlicht - Juni 2021
Peer-Review-StatusJa

Externe IDs

Scopus 85105445097
Mendeley dba7bd7f-0ffc-3118-9423-9f56ba675c55

Schlagworte