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

We present a parallelization of the revised simplex method for large extensive forms of two-stage stochastic linear programming (LP) problems. These problems have been considered too large to solve with the simplex method; instead, decomposition approaches based on Benders decomposition or, more rec...

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Bibliographic Details
Published in:	Computational optimization and applications Vol. 55; no. 3; pp. 571 - 596
Main Authors:	Lubin, Miles, Hall, J. A. Julian, Petra, Cosmin G., Anitescu, Mihai
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.07.2013 Springer Nature B.V
Subjects:	Algorithms Blocking Computation Computer science Convex and Discrete Geometry Decomposition Linear algebra Linear programming Management Science Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Methods Operations Research Operations Research/Decision Theory Optimization Random variables Simplex method Sparsity Statistics Stochasticity Studies Parallel computing Stochastic optimization Simplex method Block-angular
ISSN:	0926-6003, 1573-2894
Online Access:	Get full text
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