Results 271 to 280 of about 31,999 (310)

Learning the bistable cortical dynamics of the sleep-onset period. [PDF]

PLoS Comput Biol
Hu Z, Aravind M, Lei X, Kutz JN, Aucouturier JJ.   +4 more
europepmc   +1 more source

Decomposition methods in stochastic programming

Mathematical Programming, 1997
Stochastic programming problems have very large dimension and characteristic structures which are tractable by decomposition. We review basic ideas of cutting plane methods, augmented Lagrangian and splitting methods, and stochastic decomposition methods for convex polyhedral multi-stage stochastic programming problems..
Andrzej Ruszczynski, Ruszczynski Andrzej   +1 more
exaly   +5 more sources

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WHIRL DECOMPOSITION OF STOCHASTIC SYSTEMS

IEEE Transactions on Computers, 1971
Using a technique based on "state splitting" it is shown that every n-state Markov system is decomposable into a whirl interconnection of n−1 two-state Markov systems.
openaire   +2 more sources

Stochastic scenario decomposition for multistage stochastic programs

IMA Journal of Management Mathematics, 2009
Over the past decade, several stochastic approaches have been proposed for two-stage stochastic programs. Many of these algorithms have attractive computational as well as conceptual properties (e.g. convergence with probability one). This paper expands the realm of such approaches to multistage convex stochastic programming problems.
J. L. Higle, B. Rayco, S. Sen
openaire   +1 more source

Stochastic multiplier and divider for stochastic LU decomposition

2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2), 2017
In this paper, designing of stochastic multiplier and divider is proposed for designing of Lower-Upper decomposition (LUD) scheme. By using stochastic computation complicated operations of LUD can be performed by simple logic gates. By using stochastic multiplier and divider computational complexity is reduced. Stochastic multiplier and divider use the
K. Ferents Koni Jiavana, Nitin Gurjar
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A management system for decompositions in stochastic programming

Annals of Operations Research, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert Fourer, Leo Lopes
openaire   +1 more source

Enhancements of two-stage stochastic decomposition

Computers & Operations Research, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Suvrajeet Sen, Zhihong Zhou, Kai Huang
openaire   +1 more source

Correction to: On a decomposition for infinite stochastic matrices

Queueing Systems, 2000
An error in the proof to theorem 1 in: On a decomposition for infinite transition matrices, Queueing Systems 27 (1997) 127–130, is corrected.
Yiqiang Q. Zhao, Wei Wayne Li, W. John Braun   +2 more
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Dual decomposition in stochastic integer programming

Operations Research Letters, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carøe, Claus Carsten, Schultz, Rüdiger
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Stabilizing Stochastic Decomposition

1996
The principles developed in Chapter 3 lay the foundation for Stochastic Decomposition (SD) algorithms. We note that although the objective function approximations developed by an SD algorithm are considerably less accurate than the sample mean function, the SD approximations are sufficiently accurate to ensure asymptotic optimality for a subsequence of
Julia L. Higle, Suvrajeet Sen
openaire   +1 more source