Read more
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today's state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
List of contents
Introduction.- The Nested Distance.- Risk and Utility Functionals.- From Data to Models.- Time Consistency.- Approximations and Bounds.- The Problem of Ambiguity in Stochastic Optimization.- Examples.
About the author
Alois Pichler, born 1966, is a member of staff at the Department of Culture, Language and Information Technology (AKSIS) at UNIFOB AS, Bergen, Norway. He is Director of the Wittgenstein Archives at the University of Bergen. He is member of the Executive Committee of the Austrian Ludwig Wittgenstein Society. Homepage: http://teksttek.aksis.uib.no/people/alois.
Summary
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
Additional text
“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)
Report
"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)
