Using a Massively Parallel Processor to Solve Large Sparse Linear Programs by an Interior-Point Method

DOI10.1137/S1064827594272086zbMath0913.65048OpenAlexW2092407906MaRDI QIDQ4389258

Robert Fourer, Sanjay Mehrotra, Joseph Czyzyk

Publication date: 12 May 1998

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/s1064827594272086

zbMATH Keywords

linear programminglarge-scale optimizationparallel computationinterior-point methods

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Linear programming (90C05) Parallel numerical computation (65Y05) Numerical algorithms for specific classes of architectures (65Y10)

Related Items

An interior-point trust-funnel algorithm for nonlinear optimization, Using a Massively Parallel Processor to Solve Large Sparse Linear Programs by an Interior-Point Method, A primal-dual decomposition algorithm for multistage stochastic convex programming

Uses Software

• MINOS

Cites Work

• Solving symmetric indefinite systems in an interior-point method for linear programming
• Symmetric indefinite systems for interior point methods
• On the Implementation of a Primal-Dual Interior Point Method
• On Implementing Mehrotra’s Predictor–Corrector Interior-Point Method for Linear Programming
• Data Structures and Programming Techniques for the Implementation of Karmarkar's Algorithm
• Highly Parallel Sparse Cholesky Factorization
• Using a Massively Parallel Processor to Solve Large Sparse Linear Programs by an Interior-Point Method
• A Study of the Augmented System and Column-Splitting Approaches for Solving Two-Stage Stochastic Linear Programs by Interior-Point Methods