Approximate Subgradient Methods for Lagrangian Relaxations on Networks

DOI10.1007/978-3-642-04802-9_21zbMath1189.90158DBLPconf/ifip7/Mijangos07OpenAlexW1570543188WikidataQ57397212 ScholiaQ57397212MaRDI QIDQ3557823

Eugenio Mijangos

Publication date: 23 April 2010

Published in: IFIP Advances in Information and Communication Technology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-04802-9_21

zbMATH Keywords

convergencenetwork flowstepsizes

Mathematics Subject Classification ID

Nonlinear programming (90C30) Deterministic network models in operations research (90B10) Methods of reduced gradient type (90C52)

Uses Software

• DIMACS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On large scale nonlinear network optimization
• Convergence of some algorithms for convex minimization
• On the first-order estimation of multipliers from Kuhn-Tucker systems
• Approximate subgradient methods for nonlinearly constrained network flow problems
• Incremental Subgradient Methods for Nondifferentiable Optimization
• A Variant of the Constant Step Rule for Approximate Subgradient Methods over Nonlinear Networks
• Large-scale linearly constrained optimization
• Convergence of Approximate and Incremental Subgradient Methods for Convex Optimization

This page was built for publication: Approximate Subgradient Methods for Lagrangian Relaxations on Networks