22,99 €
inkl. MwSt.
Versandfertig in 6-10 Tagen
11 °P sammeln
Andere Kunden interessierten sich auch für
![Stochastic Computing]( "Stochastic Computing")
Stochastic Computing19,99 €![Stochastic Learning and Optimization]( "Stochastic Learning and Optimization")
Stochastic Learning and Optimization147,99 €![Stochastic Learning and Optimization]( "Stochastic Learning and Optimization")
Stochastic Learning and Optimization168,99 €![Modelling and Simulation]( "Modelling and Simulation")
Modelling and Simulation55,99 €![Performance Modeling, Stochastic Networks, and Statistical Multiplexing, Second Edition]( "Performance Modeling, Stochastic Networks, and Statistical Multiplexing, Second Edition")
Performance Modeling, Stochastic Networks, and Statistical Multiplexing, Second Edition42,79 €![Stochastic Models of Neural Networks]( "Stochastic Models of Neural Networks")
Stochastic Models of Neural Networks112,99 €![Stochastic Modeling of Microstructures]( "Stochastic Modeling of Microstructures")
Stochastic Modeling of Microstructures61,99 €
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Stochastic programming is a framework for modeling optimization problems that involve uncertainty. Whereas deterministic optimization problems are formulated with known parameters, real world problems almost invariably include some unknown parameters. When the parameters are known only within certain bounds, one approach to tackling such problems is called robust optimization. Here the goal is to find a solution which is feasible for all such data and optimal in some sense. Stochastic programming models are similar in style but take advantage of the fact that probability distributions governing the data are known or can be estimated. The goal here is to find some policy that is feasible for all (or almost all) the possible data instances and maximizes the expectation of some function of the decisions and the random variables.