Parallel distributed-memory simplex for large-scale stochastic LP problems

DOI10.1007/s10589-013-9542-yzbMath1276.90044OpenAlexW2013340830MaRDI QIDQ2393649

Miles Lubin, Mihai Anitescu, J. A. J. Hall, Cosmin G. Petra

Publication date: 8 August 2013

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://www.pure.ed.ac.uk/ws/files/17773151/Parallel_distributed_memory_simplex_for_large_scale_stochastic_LP_problems.pdf

zbMATH Keywords

stochastic optimizationparallel computingsimplex methodblock-angular

Mathematics Subject Classification ID

Linear programming (90C05) Stochastic programming (90C15) Extreme-point and pivoting methods (90C49)

Related Items (9)

Advances in the Parallelization of the Simplex Method ⋮ Parallel PIPS-SBB: multi-level parallelism for stochastic mixed-integer programs ⋮ Efficient Stochastic Programming in Julia ⋮ On proximal augmented Lagrangian based decomposition methods for dual block-angular convex composite programming problems ⋮ An augmented Lagrangian filter method ⋮ Asynchronous Lagrangian scenario decomposition ⋮ A stabilised scenario decomposition algorithm applied to stochastic unit commitment problems ⋮ A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method ⋮ Novel update techniques for the revised simplex method

Uses Software

• PIPS
• DEVEX
• SUTIL
• CSparse

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Progress in the dual simplex algorithm for solving large scale LP problems: Techniques for a fast and stable implementation
• Computational methods for solving two-stage stochastic linear programming problems
• A practical anti-cycling procedure for linearly constrained optimization
• A fast LU update for linear programming
• Active set methods for problems in column block angular form
• Steepest-edge simplex algorithms for linear programming
• Scalable parallel computations for large-scale stochastic programming
• Computational techniques of the simplex method
• Decomposition algorithms for stochastic programming on a computational grid
• Exploiting structure in parallel implementation of interior point methods for optimization
• Hyper-sparsity in the revised simplex method and how to exploit it
• The Elimination form of the Inverse and its Application to Linear Programming
• Introduction to Stochastic Programming
• Direct Methods for Sparse Linear Systems
• Sparse Partial Pivoting in Time Proportional to Arithmetic Operations
• Computing Sparse LU Factorizations for Large-Scale Linear Programming Bases
• Matrix augmentation and partitioning in the updating of the basis inverse
• Permuting Sparse Rectangular Matrices into Block-Diagonal Form
• Updated triangular factors of the basis to maintain sparsity in the product form simplex method
• A parallel direct solver for large sparse highly unsymmetric linear systems
• An Approach to Some Structured Linear Programming Problems
• Pivot selection methods of the Devex LP code
• The Product Form for the Inverse in the Simplex Method

This page was built for publication: Parallel distributed-memory simplex for large-scale stochastic LP problems