An Augmented Lagrangian Method for Cardinality-Constrained Optimization Problems

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Christian Kanzow - , University of Würzburg (Author)
  • Andreas Budi Raharja - , University of Würzburg (Author)
  • Alexandra Schwartz - , Chair of Mathematical Optimization (Author)

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

Original languageEnglish
Pages (from-to)793-813
Number of pages21
JournalJournal of Optimization Theory and Applications
Volume189
Issue number3
Publication statusPublished - Jun 2021
Peer-reviewedYes

External IDs

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

Keywords