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» Discrete stochastic optimization using linear interpolation
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WSC
2008
13 years 7 months ago
Discrete stochastic optimization using linear interpolation
We consider discrete stochastic optimization problems where the objective function can only be estimated by a simulation oracle; the oracle is defined only at the discrete points....
Honggang Wang, Bruce W. Schmeiser
ICML
2000
IEEE
14 years 5 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos
HYBRID
2007
Springer
13 years 11 months ago
Robust, Optimal Predictive Control of Jump Markov Linear Systems Using Particles
Hybrid discrete-continuous models, such as Jump Markov Linear Systems, are convenient tools for representing many real-world systems; in the case of fault detection, discrete jumps...
Lars Blackmore, Askar Bektassov, Masahiro Ono, Bri...
WSC
2000
13 years 6 months ago
Simulation optimization of stochastic systems with integer variables by sequential linearization
Discrete-event simulation is widely used to analyse and improve the performance of manufacturing systems. The related optimization problem often includes integer design variables ...
S. J. Abspoel, L. F. P. Etman, J. Vervoort, J. E. ...
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 5 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking