Convergence of Augmented Lagrangian Methods for Composite Optimization Problems

Local convergence analysis of the augmented Lagrangian method (ALM) is established for a large class of composite optimization problems with nonunique Lagrange multipliers under a second-order sufficient condition. We present a new second-order variational property called the semistability of second subderivatives and demonstrate that it is widely satisfied for numerous classes of functions, which is important for applications in constrained and composite optimization problems. Using the latter condition and a certain second-order sufficient condition, we are able to establish Q-linear convergence of the primal-dual sequence for an inexact version of the ALM for composite programs. Funding: Research of the first author is partially supported by Singapore National Academy of Science via SASEAF Programme under the grant RIE2025 NRF International Partnership Funding Initiative. Research of the second author is partially supported by the National Science Foundation under the grant DMS 2108546.

Authors

Institutions

Publication Details

Journal
Mathematics of Operations Research
Published
2025-03-14
DOI
https://doi.org/10.1287/moor.2023.0324
Citations
1
Primary Topic
Advanced Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
2.63
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Convergence of Augmented Lagrangian Methods for Composite Optimization Problems

Ebrahim Sarabi, Nguyen T. V. Hang
1 citations
Mathematics of Operations Research
Advanced Optimization Algorithms Research
2.63
article

Convergence of Augmented Lagrangian Methods for Composite Optimization Problems

Ebrahim Sarabi, Nguyen T. V. Hang
article en
1 citations

Abstract

Local convergence analysis of the augmented Lagrangian method (ALM) is established for a large class of composite optimization problems with nonunique Lagrange multipliers under a second-order sufficient condition. We present a new second-order variational property called the semistability of second subderivatives and demonstrate that it is widely satisfied for numerous classes of functions, which is important for applications in constrained and composite optimization problems. Using the latter condition and a certain second-order sufficient condition, we are able to establish Q-linear convergence of the primal-dual sequence for an inexact version of the ALM for composite programs. Funding: Research of the first author is partially supported by Singapore National Academy of Science via SASEAF Programme under the grant RIE2025 NRF International Partnership Funding Initiative. Research of the second author is partially supported by the National Science Foundation under the grant DMS 2108546.

Mathematics of Operations ResearchVol. 51(1)
Nanyang Technological University (SG), Institute of Mathematics (VN), Vietnam Academy of Science and Technology (VN), Miami University (US)
Openalex Percentile: Top 16%
Advanced Optimization Algorithms Research
2.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Convergence of Augmented Lagrangian Methods for Composite Optimization Problems — Ebrahim Sarabi, Nguyen T. V. Hang · Mathematics of Operations Research (2025) | TGRS Research Map | TGRS