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Risk Management in Stochastic Integer Programming, Frederike Neise


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Автор: Frederike Neise
Название:  Risk Management in Stochastic Integer Programming
ISBN: 9783834805478
Издательство: Springer
Классификация:
ISBN-10: 3834805475
Обложка/Формат: Paperback
Страницы: 107
Вес: 0.15 кг.
Дата издания: 28.07.2008
Язык: English
Размер: 210 x 148 x 6
Основная тема: Mathematics
Подзаголовок: With Application to Dispersed Power Generation
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: I am deeply grateful to my advisor Prof. Dr. Rudiger Schultz for his untiring - couragement. Moreover, I would like to express my gratitude to Prof. Dr. -Ing. - mund Handschin and Dr. -Ing. Hendrik Neumann from the University of Dortmund for inspiration and support. I would like to thank PD Dr. Rene Henrion from the Weierstrass Institute for Applied Analysis and Stochastics in Berlin for reviewing this thesis. Cordial thanks to my colleagues at the University of Duisburg-Essen for motivating and fruitful discussions as well as a pleasurable cooperation. Contents 1 Introduction 1 1. 1 Stochastic Optimization. . . . . . . . . . . . . . . . . . . . . . . 3 1. 1. 1 The two-stage stochastic optimization problem . . . . . . 3 1. 1. 2 Expectation-based formulation. . . . . . . . . . . . . . . 5 1. 2 Content and Structure. . . . . . . . . . . . . . . . . . . . . . . . 6 2 RiskMeasuresinTwo-StageStochasticPrograms 9 2. 1 Risk Measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2. 1. 1 Deviation measures. . . . . . . . . . . . . . . . . . . . . 10 2. 1. 2 Quantile-based risk measures . . . . . . . . . . . . . . . 11 2. 2 Mean-Risk Models . . . . . . . . . . . . . . . . . . . . . . . . . 12 2. 2. 1 Results concerning structure and stability . . . . . . . . . 13 2. 2. 2 Deterministic equivalents. . . . . . . . . . . . . . . . . . 22 2. 2. 3 Algorithmic issues - dual decomposition method . . . . . 26 3 StochasticDominanceConstraints 33 3. 1 Introduction to Stochastic Dominance . . . . . . . . . . . . . . . 33 3. 1. 1 Stochastic orders for the preference of higher outcomes . . 34 3. 1. 2 Stochastic orders for the preference of smaller outcomes . 38 3. 2 Stochastic Dominance Constraints . . . . . . . . . . . . . . . . . 42 3. 2. 1 First order stochastic dominance constraints. . . . . . . . 43 3. 2. 2 Results concerning structure and stability . . . . . . . . . 44 3. 2. 3 Deterministic equivalents. . . . . . . . . . . . . . . . . . 51 3. 2. 4 Algorithmic issues . . . . . . . . . . . . . . . . . . . . .


Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming

Автор: Uwe Gotzes
Название: Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming
ISBN: 3834808431 ISBN-13(EAN): 9783834808431
Издательство: Springer
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Цена: 14673.00 р.
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Описание: 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.

Integer Programming and Combinatorial Optimization

Автор: Karen Aardal; Bert Gerards
Название: Integer Programming and Combinatorial Optimization
ISBN: 3540422250 ISBN-13(EAN): 9783540422259
Издательство: Springer
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Цена: 10480.00 р.
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Описание: The locations and years of the seven rs t IPCO conferences were: IPCO I, Waterloo (Canada) 1990, IPCO II, Pittsburgh (USA) 1992, IPCO III, - ice (Italy) 1993, IPCO IV, Copenhagen (Denmark) 1995, IPCO V, Vancouver (Canada) 1996, IPCO VI, Houston (USA) 1998, IPCO VII, Graz (Austria) 1999.

Integer Programming and Combinatorial Optimization

Автор: William J. Cook; Andreas S. Schulz
Название: Integer Programming and Combinatorial Optimization
ISBN: 3540436766 ISBN-13(EAN): 9783540436768
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Compiled from the proceedings of the 9th International Conference on Integer Programming and Combinatorial Optimization in May 2002, this volume contains 33 papers. The topics covered include scaling algorithms, flow algorithms, combinatorial optimization algorithms and approximate TSP Solutions.

Integer Programming and Combinatorial Optimization

Автор: Egon Balas; Jens Clausen
Название: Integer Programming and Combinatorial Optimization
ISBN: 3540594086 ISBN-13(EAN): 9783540594086
Издательство: Springer
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Цена: 12577.00 р.
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Описание: This volume represents the proceedings of the Fourth International Conference on Integer Programming and Combinatorial Optimization, (IPCO) in 1995. Theoretical and algorithmic basics for the solution of optimization problems such as production planning, are presented.

Integer Programming and Combinatorial Optimization

Автор: William H. Cunningham; S. Thomas McCormick; Mauric
Название: Integer Programming and Combinatorial Optimization
ISBN: 3540613102 ISBN-13(EAN): 9783540613107
Издательство: Springer
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Цена: 11179.00 р.
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Описание: This volume presents papers from the Fifth International IPCO Conference, held in Vancouver in June 1996. The papers look at developments in theory, computation, and applications of integer programming and combinatorial optimization.

Integer Programming and Combinatorial Optimization

Автор: Gerard Cornuejols; Rainer E. Burkard; Gerhard J. W
Название: Integer Programming and Combinatorial Optimization
ISBN: 3540660194 ISBN-13(EAN): 9783540660194
Издательство: Springer
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Цена: 12577.00 р.
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Описание: These papers cover: approximation, branch and bound, cutting plane, graph and network, and online algorithms; computational biology, complexity and geometry; diaphantine equations; geometry of numbers; and polyhedral combinatorics, scheduling and semidefinite programs.

Markov Decision Processes: Discrete Stochastic Dynamic Programming

Автор: Martin L. Puterman
Название: Markov Decision Processes: Discrete Stochastic Dynamic Programming
ISBN: 0471727822 ISBN-13(EAN): 9780471727828
Издательство: Wiley
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Цена: 20584.00 р.
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Описание: This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.

Shape Optimization under Uncertainty from a Stochastic Programming Point of View

Автор: Harald Held
Название: Shape Optimization under Uncertainty from a Stochastic Programming Point of View
ISBN: 3834809098 ISBN-13(EAN): 9783834809094
Издательство: Springer
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Описание: Optimization problems whose constraints involve partial differential equations (PDEs) are relevant in many areas of technical, industrial, and economic app- cations. At the same time, they pose challenging mathematical research problems in numerical analysis and optimization. The present text is among the ?rst in the research literature addressing stochastic uncertainty in the context of PDE constrained optimization. The focus is on shape optimization for elastic bodies under stochastic loading. Analogies to ?nite dim- sional two-stage stochastic programming drive the treatment, with shapes taking the role of nonanticipative decisions.The main results concern level set-based s- chastic shape optimization with gradient methods involving shape and topological derivatives. The special structure of the elasticity PDE enables the numerical - lution of stochastic shape optimization problems with an arbitrary number of s- narios without increasing the computational effort signi?cantly. Both risk neutral and risk averse models are investigated. This monograph is based on a doctoral dissertation prepared during 2004-2008 at the Chair of Discrete Mathematics and Optimization in the Department of Ma- ematics of the University of Duisburg-Essen. The work was supported by the Deutsche Forschungsgemeinschaft (DFG) within the Priority Program "Optimi- tion with Partial Differential Equations." Rudiger Schultz Acknowledgments I owe a great deal to my supervisors, colleagues, and friends who have always supported, encouraged, andenlightenedmethroughtheirownresearch, comments, and questions.

Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming

Автор: Christian K?chler
Название: Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming
ISBN: 3834809217 ISBN-13(EAN): 9783834809216
Издательство: Springer
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Описание: Christian Kuchler studies various aspects of the stability of stochastic optimization problems as well as approximation and decomposition methods in stochastic programming. In particular, the author presents an extension of the Nested Benders decomposition algorithm related to the concept of recombining scenario trees.


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