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» Sampling Bounds for Stochastic Optimization
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MP
1998
61views more  MP 1998»
13 years 9 months ago
A branch and bound method for stochastic global optimization
Vladimir I. Norkin, Georg Ch. Pflug, Andrezj Ruszc...
INFORMATICALT
2000
104views more  INFORMATICALT 2000»
13 years 9 months ago
Nonlinear Stochastic Optimization by the Monte-Carlo Method
Methods for solving stochastic optimization problems by Monte-Carlo simulation are considered. The stoping and accuracy of the solutions is treated in a statistical manner, testing...
Leonidas Sakalauskas
CORR
2011
Springer
168views Education» more  CORR 2011»
13 years 4 months ago
Limit Theorems for the Sample Entropy of Hidden Markov Chains
The Shannon-McMillan-Breiman theorem asserts that the sample entropy of a stationary and ergodic stochastic process converges to the entropy rate of the same process almost surely...
Guangyue Han
CCE
2004
13 years 9 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
ORL
2008
124views more  ORL 2008»
13 years 9 months ago
Sample average approximation of expected value constrained stochastic programs
We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio s...
Wei Wang, Shabbir Ahmed