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Generalized Bounds for Convex Multistage Stochastic Programs

  • Book
  • © 2005

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Authors:
  1. Daniel Kuhn

    1. Institut für Unternehmensforschung (HSG), Universität St. Gallen, St. Gallen, Switzerland

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Editors:
  1. M. Beckmann
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  2. H. P. Künzi
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  3. G. Fandel

    1. Fachbereich Wirtschaftswissenschaften, Fernuniversität Hagen, Hagen, Germany

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  4. W. Trockel

    1. Institut für Mathematische Wirtschaftsforschung (IMW), Universität Bielefeld, Bielefeld, Germany

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  5. A. Basile
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  6. A. Drexl
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  7. H. Dawid
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  8. K. Inderfurth
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  9. W. Kürsten
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  10. U. Schittko
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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 548)

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Table of contents (7 chapters)

  1. Front Matter

    Pages I-XI
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  2. Introduction

    Pages 1-6

  3. Basic Theory of Stochastic Optimization

    Pages 7-27

  4. Convex Stochastic Programs

    Pages 29-49

  5. Barycentric Approximation Scheme

    Pages 51-81

  6. Extensions

    Pages 83-112

  7. Applications in the Power Industry

    Pages 113-140

  8. Conclusions

    Pages 141-146

  9. Back Matter

    Pages 147-196
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Keywords

About this book

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.

Authors, Editors and Affiliations

  • Fachbereich Wirtschaftswissenschaften, Fernuniversität Hagen, Hagen, Germany

    G. Fandel

  • Institut für Mathematische Wirtschaftsforschung (IMW), Universität Bielefeld, Bielefeld, Germany

    W. Trockel

  • Institut für Unternehmensforschung (HSG), Universität St. Gallen, St. Gallen, Switzerland

    Daniel Kuhn

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