Stochastic Programming, I.M. Stancu-Minasian

Автор: Shreve
Название: Stochastic Calculus for Finance I
ISBN: 0387401008 ISBN-13(EAN): 9780387401003
Издательство: Springer
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Описание: Developed for the professional Master`s program in Computational Finance at Carnegie Mellon, the leading financial engineering program in the U.S. Has been tested in the classroom and revised over a period of several yearsExercises conclude every chapter;

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: 137230.00 T
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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.

Автор: Gerd Infanger
Название: Stochastic Programming
ISBN: 1461427622 ISBN-13(EAN): 9781461427629
Издательство: Springer
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Описание: Management Science published in 2005 a special volume featuring the "Ten most Influential Papers of the first 50 Years of Management Science." George Dantzig`s original 1955 stochastic programming paper, "Linear Programming under Uncertainty," was featured among these ten.

Автор: Masatoshi Sakawa; Ichiro Nishizaki; Hideki Katagir
Название: Fuzzy Stochastic Multiobjective Programming
ISBN: 1461428068 ISBN-13(EAN): 9781461428060
Издательство: Springer
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Описание: With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.

Автор: Masatoshi Sakawa; Hitoshi Yano; Ichiro Nishizaki
Название: Linear and Multiobjective Programming with Fuzzy Stochastic Extensions
ISBN: 1489978550 ISBN-13(EAN): 9781489978554
Издательство: Springer
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Описание: This self-contained book offers comprehensive coverage of linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, with applications in purchase and transportation planning for food retailing.

Автор: Andr?s Pr?kopa
Название: Stochastic Programming
ISBN: 0792334825 ISBN-13(EAN): 9780792334828
Издательство: Springer
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Описание: Stochastic programming - the science that provides us with tools to design and control stochastic systems with the aid of mathematical programming techniques - lies at the intersection of statistics and mathematical programming. This book offers a comprehensive introduction to the field and its basic mathematical tools.

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: 97820.00 T
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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.

Автор: Frederike Neise
Название: Risk Management in Stochastic Integer Programming
ISBN: 3834805475 ISBN-13(EAN): 9783834805478
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Цена: 65210.00 T
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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 . . . . . . . . . . . . . . . . . . . . .

Автор: Peter Kall; J?nos Mayer
Название: Stochastic Linear Programming
ISBN: 1461427452 ISBN-13(EAN): 9781461427452
Издательство: Springer
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Цена: 46570.00 T
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Описание: Authored by two of the field`s most prominent researchers, this new edition has been comprehensively updated, with new material on contemporary models and methods including stochastic DEA models, material on Sharpe-ratio, and asset liability management.

Автор: Kurt Marti; Peter Kall
Название: Stochastic Programming
ISBN: 3540589961 ISBN-13(EAN): 9783540589969
Издательство: Springer
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Цена: 81050.00 T
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Описание: Proceedings of the 2nd GAMM/IFIP-Workshop on "Stochastic Optimization:Numerical Methods and Technical Applications" held at the Federal Armed Forces University, Munich, Neubiberg/Munchen, Germany, June 15-17, 1993

Автор: Kurt Marti; Peter Kall
Название: Stochastic Programming Methods and Technical Applications
ISBN: 3540639241 ISBN-13(EAN): 9783540639244
Издательство: Springer
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Цена: 93160.00 T
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Описание: Optimization problems arising in practice usually contain several random parameters. The original problem with random parameters must be replaced by an appropriate deterministic substitute problem, and efficient numerical solution or approximation techniques have to be developed for those problems.

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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Цена: 97820.00 T
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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.