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SIAMCO
2002
92views more  SIAMCO 2002»
13 years 7 months ago
Numerical Approximations for Stochastic Differential Games
The Markov chain approximation method is a widely used, relatively easy to use, and efficient family of methods for the bulk of stochastic control problems in continuous time, for...
Harold J. Kushner
SIAMCO
2008
72views more  SIAMCO 2008»
13 years 7 months ago
Optimal Consumption in a Growth Model with the Cobb--Douglas Production Function
An optimal consumption problem is studied in a growth model for the Cobb-Douglas production function in a finite horizon. The problem is transfered into a stochastic Ramsey proble...
Hiroaki Morimoto, Xun Yu Zhou
INFORMATICALT
2000
104views more  INFORMATICALT 2000»
13 years 7 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
FSTTCS
2006
Springer
13 years 11 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys
MP
2006
175views more  MP 2006»
13 years 7 months ago
Conditional Value-at-Risk in Stochastic Programs with Mixed-Integer Recourse
In classical two-stage stochastic programming the expected value of the total costs is minimized. Recently, mean-risk models - studied in mathematical finance for several decades -...
Rüdiger Schultz, Stephan Tiedemann