An augmented Lagrangian decomposition method for block diagonal linear programming problems

DOI10.1016/0167-6377(89)90055-2zbMath1418.90156OpenAlexW2142574689MaRDI QIDQ2314414

Ruszczyński, Andrzej

Publication date: 22 July 2019

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6377(89)90055-2

zbMATH Keywords

linear programmingdecompositionaugmented Lagrangians

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Linear programming (90C05)

Related Items

On the enrouting protocol problem under uncertainty, A smooth penalty function algorithm for network-structured problems, Global Complexity Bound of a Proximal ADMM for Linearly Constrained Nonseparable Nonconvex Composite Programming, Decomposition techniques with mixed integer programming and heuristics for home healthcare planning, Karush-Kuhn-Tucker transformation approach to multi-level linear programming problems., A diagonal quadratic approximation method for large scale linear programs, A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method, Total allowable catch for managing squat lobster fishery using stochastic nonlinear programming, Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems, Modelling and analysis of multistage stochastic programming problems: A software environment, KKT transformation approach for multi-objective multi-level linear programming problems

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Decomposition in large system optimization using the method of multipliers
• Parallel decomposition of multistage stochastic programming problems
• Multiplier and gradient methods
• Decomposition Principle for Linear Programs
• Scenarios and Policy Aggregation in Optimization Under Uncertainty
• A regularized decomposition method for minimizing a sum of polyhedral functions
• Restricted simplicial decomposition: Computation and extensions
• A finite algorithm to maximize certain pseudoconcave functions on polytopes
• Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
• An extension of the frank and Wolfe method of feasible directions
• A new method for the optimization of a nonlinear function subject to nonlinear constraints
• Elements of Large-Scale Mathematical Programming Part I: Concepts