| Issue |
RAIRO-Oper. Res.
Volume 51, Number 1, January-March 2017
|
|
|---|---|---|
| Page(s) | 17 - 41 | |
| DOI | https://doi.org/10.1051/ro/2015065 | |
| Published online | 05 December 2016 | |
A survey on operator splitting and decomposition of convex programs
1 EDF R& D, Clamart, France.
2 Laboratoire d’Informatique, de Modélisation et d’Optimisation des Systèmes, (L.I.M.O.S), Clermont Université, Clermont-Ferrand France
philippe.mahey@isima.fr
Received: 13 August 2015
Accepted: 21 December 2015
Many structured convex minimization problems can be modeled by the search of a zero of the sum of two monotone operators. Operator splitting methods have been designed to decompose and regularize at the same time these kind of models. We review here these models and the classical splitting methods. We focus on the numerical sensitivity of these algorithms with respect to the scaling parameters that drive the regularizing terms, in order to accelerate convergence rates for different classes of models.
Mathematics Subject Classification: 65K13 / 90C25 / 90C30
Key words: Operator splitting / Augmented Lagrangian / Decomposition methods
© EDP Sciences, ROADEF, SMAI 2016
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