Stability Approximation And Decomposition In Two And Multistage Stochastic Programming
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Stability Approximation And Decomposition In Two And Multistage Stochastic Programming
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Author : Christian Küchler
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-30
Stability Approximation And Decomposition In Two And Multistage Stochastic Programming written by Christian Küchler and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-30 with Mathematics categories.
Christian Küchler 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.
Stochastic Decomposition
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Author : Julia L. Higle
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-02-29
Stochastic Decomposition written by Julia L. Higle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-02-29 with Business & Economics categories.
This book summarizes developments related to a class of methods called Stochastic Decomposition (SD) algorithms, which represent an important shift in the design of optimization algorithms. Unlike traditional deterministic algorithms, SD combines sampling approaches from the statistical literature with traditional mathematical programming constructs (e.g. decomposition, cutting planes etc.). This marriage of two highly computationally oriented disciplines leads to a line of work that is most definitely driven by computational considerations. Furthermore, the use of sampled data in SD makes it extremely flexible in its ability to accommodate various representations of uncertainty, including situations in which outcomes/scenarios can only be generated by an algorithm/simulation. The authors report computational results with some of the largest stochastic programs arising in applications. These results (mathematical as well as computational) are the `tip of the iceberg'. Further research will uncover extensions of SD to a wider class of problems. Audience: Researchers in mathematical optimization, including those working in telecommunications, electric power generation, transportation planning, airlines and production systems. Also suitable as a text for an advanced course in stochastic optimization.
Encyclopedia Of Optimization
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Author : Christodoulos A. Floudas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-04
Encyclopedia Of Optimization written by Christodoulos A. Floudas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-04 with Mathematics categories.
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Stochastic Multi Stage Optimization
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Author : Pierre Carpentier
language : en
Publisher:
Release Date : 2015
Stochastic Multi Stage Optimization written by Pierre Carpentier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.
Innovative Modellierung Und Optimierung Von Energiesystemen
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Author : Rüdiger Schultz
language : de
Publisher: LIT Verlag Münster
Release Date : 2009
Innovative Modellierung Und Optimierung Von Energiesystemen written by Rüdiger Schultz and has been published by LIT Verlag Münster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Economics categories.
Operations Research Proceedings 2006
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Author : Karl-Heinz Waldmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-11
Operations Research Proceedings 2006 written by Karl-Heinz Waldmann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-11 with Business & Economics categories.
This volume contains a selection of papers referring to lectures presented at the symposium Operations Research 2006 held at the University of Karlsruhe. The symposium presented the state of the art in Operations Research and related areas in Economics, Mathematics, and Computer Science and demonstrated the broad applicability of its core themes, placing particular emphasis on Basel II, one of the most topical challenges of Operations Research.
Decision Making Under Uncertainty
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Author : Claude Greengard
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Decision Making Under Uncertainty written by Claude Greengard and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.
Stochastic Programming
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Author : Gerd Infanger
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-10
Stochastic Programming written by Gerd Infanger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-10 with Mathematics categories.
From the Preface... The preparation of this book started in 2004, when George B. Dantzig and I, following a long-standing invitation by Fred Hillier to contribute a volume to his International Series in Operations Research and Management Science, decided finally to go ahead with editing a volume on stochastic programming. The field of stochastic programming (also referred to as optimization under uncertainty or planning under uncertainty) had advanced significantly in the last two decades, both theoretically and in practice. George Dantzig and I felt that it would be valuable to showcase some of these advances and to present what one might call the state-of- the-art of the field to a broader audience. We invited researchers whom we considered to be leading experts in various specialties of the field, including a few representatives of promising developments in the making, to write a chapter for the volume. Unfortunately, to the great loss of all of us, George Dantzig passed away on May 13, 2005. Encouraged by many colleagues, I decided to continue with the book and edit it as a volume dedicated to George Dantzig. 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. Hearing about this, George Dantzig suggested that his 1955 paper be the first chapter of this book. The vision expressed in that paper gives an important scientific and historical perspective to the book. Gerd Infanger
Methods Of Nonsmooth Optimization In Stochastic Programming
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Author : Wim Stefanus van Ackooij
language : en
Publisher: Springer Nature
Release Date : 2025-05-05
Methods Of Nonsmooth Optimization In Stochastic Programming written by Wim Stefanus van Ackooij and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-05 with Business & Economics categories.
This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty. Each method is accompanied by rigorous mathematical analysis, ensuring a deep understanding of the underlying principles. The theoretical discussions included are essential for comprehending the mechanics of various algorithms and the nature of the solutions they provide—whether they are global, local, stationary, or critical. The book begins by introducing fundamental tools from set-valued analysis, optimization, and probability theory. It then transitions from deterministic to stochastic optimization, starting with a thorough discussion of modeling, understanding uncertainty, and incorporating it into optimization problems. Following this foundation, the book explores numerical algorithms for nonsmooth optimization, covering well-known decomposition techniques and algorithms for convex optimization, mixed-integer convex programming, and nonconvex optimization. Additionally, it introduces numerical algorithms specifically for stochastic programming, focusing on stochastic programming with recourse, chance-constrained optimization, and detailed algorithms for both risk-neutral and risk-averse multistage stochastic programs. The book guides readers through the entire process, from defining optimization models for practical problems to presenting implementable algorithms that can be applied in practice. It is intended for students, practitioners, and scholars who may be unfamiliar with stochastic programming and nonsmooth optimization. The analyses provided are also valuable for practitioners who may not be interested in convergence proofs but wish to understand the nature of the solutions obtained.
System Modeling And Optimization Xx
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Author : E.W. Sachs
language : en
Publisher: Springer
Release Date : 2013-03-14
System Modeling And Optimization Xx written by E.W. Sachs and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Technology & Engineering categories.
System Modeling and Optimization XX deals with new developments in the areas of optimization, optimal control and system modeling. The themes range across various areas of optimization: continuous and discrete, numerical and analytical, finite and infinite dimensional, deterministic and stochastic, static and dynamic, theory and applications, foundations and case studies. Besides some classical topics, modern areas are also presented in the contributions, including robust optimization, filter methods, optimization of power networks, data mining and risk control. This volume contains invited and selected papers from presentations at the 20th IFIP TC7 Conference on System Modeling and Optimization, which took place at the University of Trier, Germany from July 23 to 27, 2001, and which was sponsored by the International Federation for Information Processing (IFIP).