Alternating forward–backward splitting for linearly constrained optimization problems

Cesare Molinari, Juan Peypouquet*, Fernando Roldan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)


We present an alternating forward–backward splitting method for solving linearly constrained structured optimization problems. The algorithm takes advantage of the separable structure and possibly asymmetric regularity properties of the objective functions involved. We also describe some applications to the study of non-Newtonian fluids and image reconstruction problems. We conclude with a numerical example, and its comparison with Condat’s algorithm. An acceleration heuristic is also briefly outlined.

Original languageEnglish
Pages (from-to)1071-1088
Number of pages18
JournalOptimization letters
Issue number5
Publication statusPublished - 1-Jul-2020
Externally publishedYes


  • Convex optimization
  • Forward–backward splitting
  • Structured problems

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