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The area of stochastic programming was created in the middle of the last century, following fundamental achievements in linear and nonlinear programming. However, because of the inherent difficulty of stochastic optimization problems, it took a long time until efficient solution methods were developed. In the last two decades a dramatic change in our abilities to solve stochastic programming problems took place. This Handbook Volume brings together leading experts in the most important sub-fields of stochastic programming to present a rigorous overview of basic models, methods and applications of stochastic programming. The work is intended for researchers, students, engineers and economists, who encounter in their work optimization problems involving uncertainty. Important research volume for Management Scientists, Operations Researchers, Industrial Engineers, Econometricians, and Applied Mathematicians.
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