Generalized bounds for convex multistage stochastic programs

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Generalized bounds for convex multistage stochastic programs Daniel Kuhn is available to download <table><tr><td colspan="2"><strong style="font-size:1.This material is available do download at on Daniel Kuhn's eBooks, 2em;">Generalized bounds for convex multistage stochastic programs</strong><br/>Daniel Kuhn</td></tr> <tr> <td><b>Type:</b></td> <td>eBook</td> </tr> <tr> <td><b>Released:</b></td> <td>2004</td> </tr> <tr> <td><b>Publisher:</b></td> <td>Springer</td> </tr> <tr> <td><b>Page Count:</b></td> <td>199</td> </tr> <tr> <td><b>Format:</b></td> <td>djvu</td> </tr> <tr> <td><b>Language:</b></td> <td>English</td> </tr> <tr> <td><b>ISBN-10:</b></td> <td>3540225404</td> </tr> <tr> <td><b>ISBN-13:</b></td> <td>9783540225409</td> </tr> </table> This book investigates convex multistage stochastic programs whose objective and constraint functions exhibit a generalized nonconvex dependence on the random parameters.Generalized bounds for convex ... Textbook Although the classical Jensen and Edmundson-Madansky type bounds or its extensions are generally not available for such problems, tight bounds can systematically be constructed under mild regularity conditions. A nice primal-dual symmetry property is revealed when the proposed bounding method is applied to linear stochastic programs. After having developed the theoretical concepts, exemplary real-life applications are studied. It is shown how market power, lognormal stochastic processes, and risk-aversion can be properly handled in a stochastic programming framework. Numerical experiments show that the relative gap between the bounds can be reduced to a few percent without exploding the problem size.

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