Generalized Bounds for Convex Multistage Stochastic Programs

  • Daniel Kuhn
  • M. Beckmann
  • H. P. Künzi
  • G. Fandel
  • W. Trockel
  • A. Basile
  • A. Drexl
  • H. Dawid
  • K. Inderfurth
  • W. Kürsten
  • U. Schittko

Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 548)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Pages 1-6
  3. Pages 83-112
  4. Pages 141-146
  5. Back Matter
    Pages 147-196

About this book

Introduction

This work was completed during my tenure as a scientific assistant and d- toral student at the Institute for Operations Research at the University of St. Gallen. During that time, I was involved in several industry projects in the field of power management, on the occasion of which I was repeatedly c- fronted with complex decision problems under uncertainty. Although usually hard to solve, I quickly learned to appreciate the benefit of stochastic progr- ming models and developed a strong interest in their theoretical properties. Motivated both by practical questions and theoretical concerns, I became p- ticularly interested in the art of finding tight bounds on the optimal value of a given model. The present work attempts to make a contribution to this important branch of stochastic optimization theory. In particular, it aims at extending some classical bounding methods to broader problem classes of practical relevance. This book was accepted as a doctoral thesis by the University of St. Gallen in June 2004.1 am particularly indebted to Prof. Dr. Karl Frauendorfer for - pervising my work. I am grateful for his kind support in many respects and the generous freedom I received to pursue my own ideas in research. My gratitude also goes to Prof. Dr. Georg Pflug, who agreed to co-chair the dissertation committee. With pleasure I express my appreciation for his encouragement and continuing interest in my work.

Keywords

Approximation Technique Convex Multistage Stochastic Program Nonconvexities Numerical Solution Regularization Stochastic Optimization Stochastic Processes Stochastic Programming

Authors and affiliations

  • Daniel Kuhn
    • 1
  1. 1.Institut für Unternehmensforschung (HSG)Universität St. GallenSt. GallenSwitzerland

Editors and affiliations

  • M. Beckmann
  • H. P. Künzi
  • G. Fandel
    • 1
  • W. Trockel
    • 2
  • A. Basile
  • A. Drexl
  • H. Dawid
  • K. Inderfurth
  • W. Kürsten
  • U. Schittko
  1. 1.Fachbereich WirtschaftswissenschaftenFernuniversität HagenHagenGermany
  2. 2.Institut für Mathematische Wirtschaftsforschung (IMW)Universität BielefeldBielefeldGermany

Bibliographic information

  • DOI https://doi.org/10.1007/b138260
  • Copyright Information Springer-Verlag Berlin Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-22540-9
  • Online ISBN 978-3-540-26901-4
  • Series Print ISSN 0075-8442
  • About this book