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SIAMJO
2002
124views more  SIAMJO 2002»
15 years 5 months ago
The Sample Average Approximation Method for Stochastic Discrete Optimization
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
Anton J. Kleywegt, Alexander Shapiro, Tito Homem-d...
ICEIS
2009
IEEE
16 years 26 days ago
A Service Composition Framework for Decision Making under Uncertainty
Proposed and developed is a service composition framework for decision-making under uncertainty, which is applicable to stochastic optimization of supply chains. Also developed is ...
Malak Al-Nory, Alexander Brodsky, Hadon Nash
AUTOMATICA
2008
107views more  AUTOMATICA 2008»
15 years 6 months ago
New algorithms of the Q-learning type
We propose two algorithms for Q-learning that use the two-timescale stochastic approximation methodology. The first of these updates Q-values of all feasible state
Shalabh Bhatnagar, K. Mohan Babu
EOR
2006
104views more  EOR 2006»
15 years 6 months ago
A factor 1/2 approximation algorithm for two-stage stochastic matching problems
We introduce the two-stage stochastic maximum-weight matching problem and demonstrate that this problem is NP-complete. We give a factor 1 2 approximation algorithm and prove its ...
Nan Kong, Andrew J. Schaefer
SC
2000
ACM
15 years 10 months ago
Scalable Algorithms for Adaptive Statistical Designs
We present a scalable, high-performance solution to multidimensional recurrences that arise in adaptive statistical designs. Adaptive designs are an important class of learning al...
Robert H. Oehmke, Janis Hardwick, Quentin F. Stout