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Generalized Bounds for Convex Multistage Stochastic Programs

Daniel Kuhn
4.9/5 (14989 ratings)
Read Now Download Now ⏭ listen AudioBook
Description:This book investigates convex multistage stochastic programs whose objective and constraint functions exhibit a generalized nonconvex dependence on the random parameters. Although the classical Jensen and Edmundson-Madansky type bounds or their extensions are generally not available for such problems, tight bounds can systematically be constructed under mild regularity conditions. A distinct primal-dual symmetry property is revealed when the proposed bounding method is applied to linear stochastic programs. Exemplary applications are studied to assess the performance of the theoretical concepts in situations of practical relevance. 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 typically be reduced to a few percent at reasonable problem dimensions.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Generalized Bounds for Convex Multistage Stochastic Programs. To get started finding Generalized Bounds for Convex Multistage Stochastic Programs, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
192
Format
PDF, EPUB & Kindle Edition
Publisher
Springer Publishing Company
Release
2005
ISBN
3540269010

Generalized Bounds for Convex Multistage Stochastic Programs

Daniel Kuhn
4.4/5 (1290744 ratings)
Read Now Download now ⏭ listen AudioBook
Description: This book investigates convex multistage stochastic programs whose objective and constraint functions exhibit a generalized nonconvex dependence on the random parameters. Although the classical Jensen and Edmundson-Madansky type bounds or their extensions are generally not available for such problems, tight bounds can systematically be constructed under mild regularity conditions. A distinct primal-dual symmetry property is revealed when the proposed bounding method is applied to linear stochastic programs. Exemplary applications are studied to assess the performance of the theoretical concepts in situations of practical relevance. 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 typically be reduced to a few percent at reasonable problem dimensions.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Generalized Bounds for Convex Multistage Stochastic Programs. To get started finding Generalized Bounds for Convex Multistage Stochastic Programs, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
192
Format
PDF, EPUB & Kindle Edition
Publisher
Springer Publishing Company
Release
2005
ISBN
3540269010

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