Mar 23, 2012 · Stochastic programming is decision making under risk. This means that some of the model coefficients are random variables with known or ...

A stochastic program is an optimization problem in which some or all problem parameters are uncertain, but follow known probability distributions.

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This is the first book devoted to the full scale of applications of stochastic programming, and to provide access to publicly available algorithmic systems.

To express a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree model with associated uncertain parameters.

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This section of the book contains 21 stochastic programming applications presented in five sections: (1) production, supply chain, and scheduling; (2) gaming; ...

Stochastic programming is an optimization framework that deals with decision-making under uncertainty. A special case is two-stage stochastic programming.

This book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation.

Oct 14, 2014 · In this paper, we present an introduction to stochastic programming models and methodology at a level that is intended to be accessible to the breadth of ...