Stochastic Programming PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Stochastic Programming PDF full book. Access full book title Stochastic Programming by Horand Gassmann. Download full books in PDF and EPUB format.
Author: Horand Gassmann
Publisher: World Scientific
ISBN: 981440750X
Category : Business & Economics
Languages : en
Pages : 549
Get Book Here
Book Description
This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems.
Author: Horand Gassmann
Publisher: World Scientific
ISBN: 981440750X
Category : Business & Economics
Languages : en
Pages : 549
Get Book Here
Book Description
This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems.
Author: Christian Küchler
Publisher: Springer Science & Business Media
ISBN: 3834893994
Category : Mathematics
Languages : en
Pages : 178
Get Book Here
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.
Author: Stanford University. Department of Operations Research. Systems Optimization Laboratory
Publisher:
ISBN:
Category :
Languages : en
Pages : 52
Get Book Here
Book Description
Author: M.A.H. Dempster
Publisher: CRC Press
ISBN: 1420081926
Category : Business & Economics
Languages : en
Pages : 488
Get Book Here
Book Description
The First Collection That Covers This Field at the Dynamic Strategic and One-Period Tactical Levels. Addressing the imbalance between research and practice, Quantitative Fund Management presents leading-edge theory and methods, along with their application in practical problems encountered in the fund management industry. A Current Snapshot of State-of-the-Art Applications of Dynamic Stochastic Optimization Techniques to Long-Term Financial Planning - The first part of the book initially looks at how the quantitative techniques of the equity industry are shifting from basic Markowitz mean-variance portfolio optimization to risk management and trading applications. This section also explores novel aspects of lifetime individual consumption investment problems, fixed-mix portfolio rebalancing allocation strategies, debt management for funding mortgages and national debt, and guaranteed return fund construction. Up-to-Date Overview of Tactical Financial Planning and Risk Management - The second section covers nontrivial computational approaches to tactical fund management. This part focuses on portfolio construction and risk management at the individual security or fund manager level over the period up to the next portfolio rebalance. It discusses non-Gaussian returns, new risk-return tradeoffs, and the robustness of benchmarks and portfolio decisions. The Future Use of Quantitative Techniques in Fund Management - With contributions from well-known academics and practitioners, this volume will undoubtedly foster the recognition and wider acceptance of stochastic optimization techniques in financial practice.
Author: Gabriella Dellino
Publisher: Springer
ISBN: 1489975470
Category : Business & Economics
Languages : en
Pages : 282
Get Book Here
Book Description
This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together — as chapter contributors — researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors’ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.
Author: Alexander Shapiro
Publisher: SIAM
ISBN: 1611973422
Category : Mathematics
Languages : en
Pages : 512
Get Book Here
Book Description
Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available.? In?Lectures on Stochastic Programming: Modeling and Theory, Second Edition, the authors introduce new material to reflect recent developments in stochastic programming, including: an analytical description of the tangent and normal cones of chance constrained sets; analysis of optimality conditions applied to nonconvex problems; a discussion of the stochastic dual dynamic programming method; an extended discussion of law invariant coherent risk measures and their Kusuoka representations; and in-depth analysis of dynamic risk measures and concepts of time consistency, including several new results.?
Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 724
Get Book Here
Book Description
Author: RUSZCZYNSK
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 708
Get Book Here
Book Description
Brings together leading in the most important sub-fields of stochastic programming to present a rigourous overview of basic models, methods and applications of stochastic programming. The text is intended for researchers, students, engineers and economists, who encounter in their work optimization problems involving uncertainty.
Author: Miguel Botto-Tobar
Publisher: Springer Nature
ISBN: 3030960439
Category : Technology & Engineering
Languages : en
Pages : 432
Get Book Here
Book Description
This book constitutes the proceedings of the XVI Multidisciplinary International Congress on Science and Technology (CIT 2021), held in Quito, Ecuador, on June 14–18, 2021, proudly organized by Universidad de las Fuerzas Armadas ESPE in collaboration with GDEON. CIT is an international event with a multidisciplinary approach that promotes the dissemination of advances in science and technology research through the presentation of keynote conferences. In CIT, theoretical, technical, or application works that are research products are presented to discuss and debate ideas, experiences, and challenges. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Artificial Intelligence Computational Modeling Data Communications Defense Engineering Innovation, Technology, and Society Managing Technology & Sustained Innovation, and Business Development Security and Cryptography Software Engineering
Author: Kurt Marti
Publisher: Springer Science & Business Media
ISBN: 3642558844
Category : Science
Languages : en
Pages : 337
Get Book Here
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.
