Overview
- Provides the first comprehensive treatment of multistage stochastic decision problems
- Presents a rigorous treatment of scenario generation methods using distance concepts
- Contains new concepts of time-consistent decision making
- Showcases the influence of model ambiguity to the decision process
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Operations Research and Financial Engineering (ORFE)
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Table of contents (8 chapters)
Reviews
“As stochastic optimization problems can be solved only approximatively, the book presents the mathematical foundations for approximation methods as well as practical algorithms and examples for the generation and handling of scenario trees. … The book, covering the current status in multistage stochastic optimization, can be recommended to readers interested in theoretical as well as in practical aspects of this field.” (Kurt Marti, Mathematical Reviews, June, 2015)
Authors and Affiliations
About the authors
Georg Pflug is full professor of Statistics and Operations Research at the University of Vienna, Austria. He got a PhD in Mathematics from the University of Vienna and was Professor of Mathematics at the University of Giessen, Germany, before joining the University of Vienna as a full professor. He is author of 4 books and more than 80 peer reviewed articles. He is also editor of several books and special issues of journals.
Alois Pichler holds a PhD in economic sciences and master degrees in mathematics and physics. He has gathered business experience in different positions in the insurance and banking industry, including managerial positions. He is with the Norwegian University of Science and Technology and his scientific work is dedicated to mathematical properties of risk measures with a particular focus on their relation to insurance, and to optimization under uncertainty.Bibliographic Information
Book Title: Multistage Stochastic Optimization
Authors: Georg Ch. Pflug, Alois Pichler
Series Title: Springer Series in Operations Research and Financial Engineering
DOI: https://doi.org/10.1007/978-3-319-08843-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-08842-6Published: 27 November 2014
Softcover ISBN: 978-3-319-38267-8Published: 23 August 2016
eBook ISBN: 978-3-319-08843-3Published: 12 November 2014
Series ISSN: 1431-8598
Series E-ISSN: 2197-1773
Edition Number: 1
Number of Pages: XIV, 301
Number of Illustrations: 81 b/w illustrations
Topics: Operations Research/Decision Theory, Operations Research, Management Science, Optimization