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Stochastic Programming, Gerd Infanger


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Автор: Gerd Infanger
Название:  Stochastic Programming
ISBN: 9781461427629
Издательство: Springer
Классификация:

ISBN-10: 1461427622
Обложка/Формат: Paperback
Страницы: 388
Вес: 0.54 кг.
Дата издания: 2010
Серия: International Series in Operations Research & Management Science
Язык: English
Иллюстрации: 28 black & white tables, biography
Размер: 234 x 156 x 20
Читательская аудитория: Professional & vocational
Подзаголовок: The state of the art in honor of george b. dantzig
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


Stochastic Calculus for Finance II

Автор: Shreve, Steven E.
Название: Stochastic Calculus for Finance II
ISBN: 0387401016 ISBN-13(EAN): 9780387401010
Издательство: Springer
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Цена: 8384.00 р.
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Описание: "A wonderful display of the use of mathematical probability to derive a large set of results from a small set of assumptions.

Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 11246.00 р.
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Описание: This definitive textbook provides a solid introduction to stochastic processes, covering both theory and applications. It is written by one of the world`s leading information theorists, evolving over twenty years of graduate classroom teaching, and is accompanied by over 300 exercises, with online solutions for instructors.

Stochastic Calculus for Finance I

Автор: Shreve
Название: Stochastic Calculus for Finance I
ISBN: 0387401008 ISBN-13(EAN): 9780387401003
Издательство: Springer
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Цена: 8384.00 р.
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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;

Stochastic methods

Автор: Gardiner, Crispin W.
Название: Stochastic methods
ISBN: 3540707123 ISBN-13(EAN): 9783540707127
Издательство: Springer
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Цена: 11179.00 р.
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Описание: In the third edition of this classic the chapter on quantum Marcov processes has been replaced by a chapter on numerical treatment of stochastic differential equations to make the book even more valuable for practitioners.

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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Цена: 14673.00 р.
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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.

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.

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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Цена: 14673.00 р.
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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.

Fuzzy Stochastic Multiobjective Programming

Автор: Masatoshi Sakawa; Ichiro Nishizaki; Hideki Katagir
Название: Fuzzy Stochastic Multiobjective Programming
ISBN: 1461428068 ISBN-13(EAN): 9781461428060
Издательство: Springer
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Цена: 23757.00 р.
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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.

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.

Two-Scale Stochastic Systems / Asymptotic Analysis and Control

Автор: Kabanov Yuri, Pergamenshchikov Sergei
Название: Two-Scale Stochastic Systems / Asymptotic Analysis and Control
ISBN: 3540653325 ISBN-13(EAN): 9783540653325
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Two-scale systems described by singularly perturbed SDEs have been the subject of ample literature. However, this new monograph develops subjects that were rarely addressed and could be given the collective description "Stochastic Tikhonov-Levinson theory and its applications." The book provides a mathematical apparatus designed to analyze the dynamic behaviour of a randomly perturbed system with fast and slow variables. In contrast to the deterministic Tikhonov-Levinson theory, the basic model is described in a more realistic way by stochastic differential equations. This leads to a number of new theoretical questions but simultaneously allows us to treat in a unified way a surprisingly wide spectrum of applications like fast modulations, approximate filtering, and stochastic approximation.

Stochastic Simulation: Algorithms and Analysis

Автор: Asmussen
Название: Stochastic Simulation: Algorithms and Analysis
ISBN: 038730679X ISBN-13(EAN): 9780387306797
Издательство: Springer
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Цена: 6981.00 р.
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Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first  half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of  examples, exercises and applications students, practitioners and researchers in  probability, statistics, operations research, economics, finance, engineering  as well as biology and chemistry and physics will find the book of value.  Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of  Engineering at Stanford University. 


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