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DAGSTUHL
2007
13 years 11 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
CDC
2010
IEEE
167views Control Systems» more  CDC 2010»
13 years 5 months ago
Numerical methods for the optimization of nonlinear stochastic delay systems, and an application to internet regulation
The Markov chain approximation method is an effective and widely used approach for computing optimal values and controls for stochastic systems. It was extended to nonlinear (and p...
Harold J. Kushner
APPROX
2010
Springer
188views Algorithms» more  APPROX 2010»
13 years 11 months ago
Approximation Algorithms for Reliable Stochastic Combinatorial Optimization
We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...
Evdokia Nikolova
JAMDS
2000
90views more  JAMDS 2000»
13 years 10 months ago
Stratified filtered sampling in stochastic optimization
We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distri...
Robert Rush, John M. Mulvey, John E. Mitchell, Tho...
CDC
2009
IEEE
126views Control Systems» more  CDC 2009»
13 years 8 months ago
Stochastic optimization for Markov modulated networks with application to delay constrained wireless scheduling
Abstract-- We consider a wireless system with a small number of delay constrained users and a larger number of users without delay constraints. We develop a scheduling algorithm th...
Michael J. Neely