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Stochastic Programming, Kurt Marti; Peter Kall


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Автор: Kurt Marti; Peter Kall
Название:  Stochastic Programming
ISBN: 9783540589969
Издательство: Springer
Классификация:


ISBN-10: 3540589961
Обложка/Формат: Paperback
Страницы: 351
Вес: 0.42 кг.
Дата издания: 06.04.1995
Серия: Lecture Notes in Economics and Mathematical Systems
Язык: English
Размер: 216 x 140 x 19
Основная тема: Business and Management
Подзаголовок: Numerical Techniques and Engineering Applications
Ссылка на Издательство: Link
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Поставляется из: Германии
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


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.

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.

Stochastic Programming

Автор: Gerd Infanger
Название: Stochastic Programming
ISBN: 1461427622 ISBN-13(EAN): 9781461427629
Издательство: Springer
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Цена: 32004.00 р.
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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.

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.

BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems

Автор: Urmila Diwekar; Amy David
Название: BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems
ISBN: 1493922815 ISBN-13(EAN): 9781493922819
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems.

Linear and Multiobjective Programming with Fuzzy Stochastic Extensions

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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Цена: 10480.00 р.
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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.

Stochastic Programming

Автор: Andr?s Pr?kopa
Название: Stochastic Programming
ISBN: 0792334825 ISBN-13(EAN): 9780792334828
Издательство: Springer
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Цена: 18167.00 р.
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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.

Stochastic Two-Stage Programming

Автор: Karl Frauendorfer
Название: Stochastic Two-Stage Programming
ISBN: 3540560971 ISBN-13(EAN): 9783540560975
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Stochastic Programming offers models and methods fordecision problems wheresome of the data are uncertain. In these models the objective function isgiven as an integral, whose integrand depends on a randomvector, on its probability measure and on a decision.


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