On augmented Lagrangian decomposition methods for multistage stochastic programs

DOI10.1007/BF02187650zbMath0857.90096MaRDI QIDQ1918433

Charles H. Rosa, Ruszczyński, Andrzej

Publication date: 18 March 1997

Published in: Annals of Operations Research (Search for Journal in Brave)

zbMATH Keywords

decompositionparallel computationmultistage stochastic programmingJacobi methodaugmented Lagrangianslarge convex optimization

Mathematics Subject Classification ID

Convex programming (90C25) Stochastic programming (90C15)

Related Items (10)

A fast dual proximal-gradient method for separable convex optimization with linear coupled constraints ⋮ A preconditioning technique for Schur complement systems arising in stochastic optimization ⋮ Duality gaps in nonconvex stochastic optimization ⋮ An inexact Lagrange-Newton method for stochastic quadratic programs with recourse ⋮ Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems ⋮ Hub-and-spoke network design and fleet deployment for string planning of liner shipping ⋮ An improved L-shaped method for solving process flexibility design problems ⋮ A Lagrangian relaxation approach for stochastic network capacity expansion with budget constraints ⋮ Convergent cutting-plane and partial-sampling algorithm for multistage stochastic linear programs with recourse ⋮ Dual decomposition in stochastic integer programming

Uses Software

• MSLiP
• GAMS
• MINOS

Cites Work

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• A regularized decomposition method for minimizing a sum of polyhedral functions
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• Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
• An Extension of the DQA Algorithm to Convex Stochastic Programs
• A New Scenario Decomposition Method for Large-Scale Stochastic Optimization
• On Convergence of an Augmented Lagrangian Decomposition Method for Sparse Convex Optimization
• L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming

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