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A new partial splitting augmented Lagrangian method for minimizing the sum of three convex functions

  • Cuixia Cao
  • , Deren Han*
  • , Lingling Xu
  • *Corresponding author for this work
  • Nanjing Normal University

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a new partial splitting augmented Lagrangian method for solving the separable constrained convex programming problem where the objective function is the sum of three separable convex functions and the constraint set is also separable into three parts. The proposed algorithm combines the alternating direction method (ADM) and parallel splitting augmented Lagrangian method (PSALM), where two operators are handled by a parallel method, while the third operator and the former two are dealt with by an alternating manner. Under mild conditions, we prove the global convergence of the new method. We also report some preliminary numerical results on constrained matrix optimization problem, illustrating the advantage of the new algorithm over the most recently PADALM of Peng and Wu (2010) [12].

Original languageEnglish
Pages (from-to)5449-5457
Number of pages9
JournalApplied Mathematics and Computation
Volume219
Issue number10
DOIs
StatePublished - 2013
Externally publishedYes

Keywords

  • Alternating direction method
  • Convex programming
  • Parallel splitting
  • Penalty parameter
  • Separable structure

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