Multistage Stochastic Optimization

Multistage Stochastic Optimization PDF Author: Georg Ch. Pflug
Publisher: Springer
ISBN: 3319088432
Category : Business & Economics
Languages : en
Pages : 309

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Book Description
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.

Multistage Stochastic Optimization

Multistage Stochastic Optimization PDF Author: Georg Ch. Pflug
Publisher: Springer
ISBN: 3319088432
Category : Business & Economics
Languages : en
Pages : 309

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Book Description
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.

Stochastic Programming

Stochastic Programming PDF Author: Gerd Infanger
Publisher: Springer Science & Business Media
ISBN: 1441916423
Category : Mathematics
Languages : en
Pages : 373

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Book Description
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

Stochastic Algorithms: Foundations and Applications

Stochastic Algorithms: Foundations and Applications PDF Author: Osamu Watanabe
Publisher: Springer Science & Business Media
ISBN: 3642049435
Category : Computers
Languages : en
Pages : 230

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Book Description
The 5th Symposium on Stochastic Algorithms, Foundations and Applications (SAGA 2009) took place during October 26–28, 2009, at Hokkaido University, Sapporo(Japan).ThesymposiumwasorganizedbytheDivisionofComputerS- ence,GraduateSchoolofComputerScienceandTechnology,HokkaidoUniversity. It o?ered the opportunity to present original research on the design and analysis of randomized algorithms, random combinatorialstructures, implem- tation, experimental evaluation and real-world application of stochastic al- rithms/heuristics. In particular, the focus of the SAGA symposia series is on investigating the power of randomization in algorithms, and on the theory of stochastic processes especially within realistic scenarios and applications. Thus, the scope ofthe symposiumrangesfromthe study oftheoreticalfundamentals of randomizedcomputationtoexperimentalinvestigationsonalgorithms/heuristics and related stochastic processes. The SAGA symposium series is a biennial meeting. Previous SAGA s- posiatookplaceinBerlin,Germany(2001,LNCSvol.2264),Hat?eld,UK(2003, LNCS vol. 2827), Moscow, Russia (2005, LNCS vol. 3777), and Zur ¨ ich, Switz- land (2007, LNCS vol. 4665). This year 22 submissions were received, and the Program Committee selected 15 submissions for presentation. All papers were evaluated by at least three members of the ProgramCommittee, partly with the assistance of subreferees. The present volume contains the texts of the 15 papers presented at SAGA 2009, divided into groups of papers on learning, graphs, testing, optimization, and caching as well as on stochastic algorithms in bioinformatics.

Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition

Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition PDF Author:
Publisher: ScholarlyEditions
ISBN: 1464964785
Category : Mathematics
Languages : en
Pages : 1531

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Book Description
Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Logic, Operations, and Computational Mathematics and Geometry. The editors have built Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Logic, Operations, and Computational Mathematics and Geometry in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Logic, Operations, and Computational Mathematics and Geometry: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Modeling with Stochastic Programming

Modeling with Stochastic Programming PDF Author: Alan J. King
Publisher: Springer Nature
ISBN: 3031545508
Category :
Languages : en
Pages : 213

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Book Description


A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs

A Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs PDF Author: Debora Mahlke
Publisher: Springer Science & Business Media
ISBN: 3834898295
Category : Mathematics
Languages : en
Pages : 194

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Book Description
Motivated by practical optimization problems occurring in energy systems with regenerative energy supply, Debora Mahlke formulates and analyzes multistage stochastic mixed-integer models. For their solution, the author proposes a novel decomposition approach which relies on the concept of splitting the underlying scenario tree into subtrees. Based on the formulated models from energy production, the algorithm is computationally investigated and the numerical results are discussed.

Stochastic Optimization Methods in Finance and Energy

Stochastic Optimization Methods in Finance and Energy PDF Author: Marida Bertocchi
Publisher: Springer Science & Business Media
ISBN: 1441995862
Category : Business & Economics
Languages : en
Pages : 480

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Book Description
This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and practitioners, who cooperated in recent years to facilitate the growing penetration of stochastic programming techniques in real-world applications, inducing a significant advance over a large spectrum of complex decision problems. After the recent widespread liberalization of the energy sector in Europe and the unprecedented growth of energy prices in international commodity markets, we have witnessed a significant convergence of strategic decision problems in the energy and financial sectors. This has often resulted in common open issues and has induced a remarkable effort by the industrial and scientific communities to facilitate the adoption of advanced analytical and decision tools. The main concerns of the financial community over the last decade have suddenly penetrated the energy sector inducing a remarkable scientific and practical effort to address previously unforeseeable management problems. Stochastic Optimization Methods in Finance and Energy: New Financial Products and Energy Markets Strategies aims to include in a unified framework for the first time an extensive set of contributions related to real-world applied problems in finance and energy, leading to a common methodological approach and in many cases having similar underlying economic and financial implications. Part 1 of the book presents 6 chapters related to financial applications; Part 2 presents 7 chapters on energy applications; and Part 3 presents 5 chapters devoted to specific theoretical and computational issues.

Dynamic Stochastic Optimization

Dynamic Stochastic Optimization PDF Author: Kurt Marti
Publisher: Springer Science & Business Media
ISBN: 3642558844
Category : Science
Languages : en
Pages : 337

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Book Description
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in that may have a nonsmooth and even discontinuous character - the tegrands typical situation for "hit-or-miss" type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.

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

Stability, Approximation, and Decomposition in Two- and Multistage Stochastic Programming PDF Author: Christian Küchler
Publisher: Springer Science & Business Media
ISBN: 3834893994
Category : Mathematics
Languages : en
Pages : 178

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Book Description
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.

Optimization in Green Sustainability and Ecological Transition

Optimization in Green Sustainability and Ecological Transition PDF Author: Maurizio Bruglieri
Publisher: Springer Nature
ISBN: 3031476867
Category :
Languages : en
Pages : 366

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Book Description