Article ID: | iaor20132755 |
Volume: | 55 |
Issue: | 1 |
Start Page Number: | 75 |
End Page Number: | 111 |
Publication Date: | May 2013 |
Journal: | Computational Optimization and Applications |
Authors: | Diehl Moritz, Tran Dinh Quoc, Savorgnan Carlo |
Keywords: | programming: convex |
A new algorithm for solving large‐scale convex optimization problems with a separable objective function is proposed. The basic idea is to combine three techniques: Lagrangian dual decomposition, excessive gap and smoothing. The main advantage of this algorithm is that it automatically and simultaneously updates the smoothness parameters which significantly improves its performance. The convergence of the algorithm is proved under weak conditions imposed on the original problem. The rate of convergence is