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Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming (Stochastic Programming) - Softcover
Synopsis
Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. He illustrates the superiority of the proposed decomposition method over standard solvers for example with numerical experiments with instances from energy investment.
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From the Back Cover
Two-stage stochastic programming models are considered as attractive tools for making optimal decisions under uncertainty. Traditionally, optimality is formalized by applying statistical parameters such as the expectation or the conditional value at risk to the distributions of objective values.
Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. These stochastic orders enable the incorporation of the characteristics of whole distributions into the decision process. The profit or cost distributions must pass a benchmark test with a given acceptable distribution. Thus, additional objectives can be optimized. For this new class of stochastic optimization problems, results on structure and stability are proven and a tailored algorithm to tackle large problem instances is developed. The implications of the modelling background and numerical results from the application of the proposed algorithm are demonstrated with case studies from energy trading.
About the Author
Dr. Uwe Gotzes completed his doctoral thesis at the Department of Mathematics at the University of Duisburg-Essen. He is a network planner at E.ON Gastransport.
"About this title" may belong to another edition of this title.
- PublisherVieweg+Teubner Verlag
- Publication date2009
- ISBN 10 3834808431
- ISBN 13 9783834808431
- BindingPaperback
- LanguageEnglish
- Number of pages104
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Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming
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Decision Making With Dominance Constraints In Two-Stage Stochastic Integer Programming (Stochastic Programming) [Taschenbuch] Levesley, Jeremy; Marletta, Marco und Gotzes, Uwe
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Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming
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Vieweg+Teubner, Vieweg+Teubner Verlag Jul 2009, 2009
ISBN 10: 3834808431
ISBN 13: 9783834808431
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Two-stage stochastic programming models are considered as attractive tools for making optimal decisions under uncertainty. Traditionally, optimality is formalized by applying statistical parameters such as the expectation or the conditional value at risk to the distributions of objective values. Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. These stochastic orders enable the incorporation of the characteristics of whole distributions into the decision process. The profit or cost distributions must pass a benchmark test with a given acceptable distribution. Thus, additional objectives can be optimized. For this new class of stochastic optimization problems, results on structure and stability are proven and a tailored algorithm to tackle large problem instances is developed. The implications of the modelling background and numerical results from the application of the proposed algorithm are demonstrated with case studies from energy trading. 100 pp. Englisch. Seller Inventory # 9783834808431
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Two-stage stochastic programming models are considered as attractive tools for making optimal decisions under uncertainty. Traditionally, optimality is formalized by applying statistical parameters such as the expectation or the conditional value at risk to the distributions of objective values. Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. These stochastic orders enable the incorporation of the characteristics of whole distributions into the decision process. The profit or cost distributions must pass a benchmark test with a given acceptable distribution. Thus, additional objectives can be optimized. For this new class of stochastic optimization problems, results on structure and stability are proven and a tailored algorithm to tackle large problem instances is developed. The implications of the modelling background and numerical results from the application of the proposed algorithm are demonstrated with case studies from energy trading. Seller Inventory # 9783834808431
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Uwe Gotzes completed his doctoral thesis at the Department of Mathematics at the University of Duisburg-Essen. He is a network planner at E.ON Gastransport.Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based up. Seller Inventory # 5379307
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Decision Making With Dominance Constraints In Two-Stage Stochastic Integer Programming
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