Generalized bounds for convex multistage stochastic programs

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 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.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• ISBN: 9783540225409 ; 3540225404
• Dimensions: 24 cm
• Extent: XI, 190 S.
• Language: Englisch
• Notes: graph. Darst. ; Literaturverz. S. 175 - 181

References and Relationships

• Bibliographic citation: Lecture notes in economics and mathematical systems ; Vol. 548

Classification and Topics

• Classification: Mathematik ; Wirtschaft
• Keyword: Stochastische Optimierung ; Approximation ; Regularisierung ; Numerisches Verfahren

Contributors, Places and Time

• Event: Veröffentlichung
• (where): Berlin, Heidelberg, New York
• (who): Springer
• (when): 2005
• Creator: Kuhn, Daniel

Further information

• Table of contents: https://d-nb.info/971632340/04
• Rights: Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
• Last update: 11.03.2025, 12:28 PM CET