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.
General
Imprint: |
Springer-Verlag
|
Country of origin: |
Germany |
Series: |
Lecture Notes in Economics and Mathematical Systems, 548 |
Release date: |
October 2004 |
First published: |
2005 |
Authors: |
Daniel Kuhn
|
Dimensions: |
234 x 156 x 13mm (L x W x T) |
Format: |
Paperback
|
Pages: |
190 |
Edition: |
2005 ed. |
ISBN-13: |
978-3-540-22540-9 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Probability & statistics
Promotions
|
LSN: |
3-540-22540-4 |
Barcode: |
9783540225409 |
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