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» Sampling Bounds for Stochastic Optimization
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MP
1998
61views more  MP 1998»
14 years 11 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»
14 years 11 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»
14 years 6 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
14 years 11 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»
14 years 11 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