A global approach to crew-pairing optimization
IBM Systems Journal
Practical Parallel Algorithms for Dynamic Data Redistribution, Median Finding, and Selection
IPPS '96 Proceedings of the 10th International Parallel Processing Symposium
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Computational results with a primal-dual subproblem simplex method
Operations Research Letters
An automated approach to quality-aware web applications
Enterprise information systems IV
Generalized Column Generation for Linear Programming
Management Science
Robust Airline Fleet Assignment: Imposing Station Purity Using Station Decomposition
Transportation Science
Robust Airline Fleet Assignment: Imposing Station Purity Using Station Decomposition
Transportation Science
A Parallel Implementation of the Simplex Function Minimization Routine
Computational Economics
A new efficient parallel revised relaxation algorithm
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
A dual ascent procedure for the set partitioning problem
Discrete Optimization
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Recently, the primal-dual simplex method has been used to solve linear programs with a large number of columns. We present a parallel primal-dual simplex algorithm that is capable of solving linear programs with at least an order of magnitude more columns than the previous work. The algorithm repeatedly solves several linear programs in parallel and combines the dual solutions to obtain a new dual feasible solution. The primal part of the algorithm involves a new randomized pricing strategy. We tested the algorithm on instances with thousands of rows and tens of millions of columns. For example, an instance with 1700 rows and 45 million columns was solved in about 2 h on 12 processors.