A merit function approach to the subgradient method with averaging

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


We consider a version of the subgradient method for convex nonsmooth optimization involving subgradient averaging. Using a merit function approach in the space of decisions and subgradient estimates, we prove convergence of the primal variables to an optimal solution and of the dual variables to an optimal subgradient. Application to dual convex optimization problems is discussed.

Original languageEnglish (US)
Pages (from-to)161-172
Number of pages12
JournalOptimization Methods and Software
Issue number1
StatePublished - Feb 2008

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Optimization
  • Applied Mathematics


  • Convex optimization
  • Dual methods
  • Nonsmooth optimization
  • Subgradient method


Dive into the research topics of 'A merit function approach to the subgradient method with averaging'. Together they form a unique fingerprint.

Cite this