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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Vydané v:	Computational optimization and applications Ročník 55; číslo 3; s. 571 - 596
Hlavní autori:	Lubin, Miles, Hall, J. A. Julian, Petra, Cosmin G., Anitescu, Mihai
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.07.2013 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
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