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Decomposition And Importance Sampling For Stochastic Linear Models
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Book Synopsis Decomposition and Importance Sampling for Stochastic Linear Models by : International Business Machines Corporation. Research Division
Download or read book Decomposition and Importance Sampling for Stochastic Linear Models written by International Business Machines Corporation. Research Division and published by . This book was released on 1990 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Stanford University. Department of Operations Research. Systems Optimization Laboratory Publisher : ISBN 13 : Total Pages :52 pages Book Rating :4.F/5 ( download)
Book Synopsis Decomposition and (importance) Sampling Techniques for Multi-stage Stochastic Linear Programs by : Stanford University. Department of Operations Research. Systems Optimization Laboratory
Download or read book Decomposition and (importance) Sampling Techniques for Multi-stage Stochastic Linear Programs written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1993 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Decomposition and (importance) Sampling Techniques for Multi-stage Stochastic Linear Programs by :
Download or read book Decomposition and (importance) Sampling Techniques for Multi-stage Stochastic Linear Programs written by and published by . This book was released on 1993 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The difficulty of solving large-scale multi-stage stochastic linear programs arises from the sheer number of scenarios associated with numerous stochastic parameters. The number of scenarios grows exponentially with the number of stages and problems get easily out of hand even for very moderate numbers of stochastic parameters per stage. Our method combines dual (Benders) decomposition with Monte Carlo sampling techniques. We employ importance sampling to efficiently obtain accurate estimates of both expected future costs and gradients and right-hand sides of cuts. The method enables us to solve practical large-scale problems with many stages and numerous stochastic parameters per stage. We discuss the theory of sharing and adjusting cuts between different scenarios in a stage. We derive probabilistic lower and upper bounds, where we use importance path sampling for the upper bound estimation. Initial numerical results turned out to be promising.
Book Synopsis Planning Under Uncertainty Solving Large-scale Stochastic Linear Programs by :
Download or read book Planning Under Uncertainty Solving Large-scale Stochastic Linear Programs written by and published by . This book was released on 1992 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many practical problems, solutions obtained from deterministic models are unsatisfactory because they fail to hedge against certain contingencies that may occur in the future. Stochastic models address this shortcoming, but up to recently seemed to be intractable due to their size. Recent advances both in solution algorithms and in computer technology now allow us to solve important and general classes of practical stochastic problems. We show how large-scale stochastic linear programs can be efficiently solved by combining classical decomposition and Monte Carlo (importance) sampling techniques. We discuss the methodology for solving two-stage stochastic linear programs with recourse, present numerical results of large problems with numerous stochastic parameters, show how to efficiently implement the methodology on a parallel multi-computer and derive the theory for solving a general class of multi-stage problems with dependency of the stochastic parameters within a stage and between different stages.
Book Synopsis Planning Under Uncertainty by : Gerd Infanger
Download or read book Planning Under Uncertainty written by Gerd Infanger and published by Boyd & Fraser Publishing Company. This book was released on 1994 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization in Planning and Operation of Electric Power Systems by : Karl Frauendorfer
Download or read book Optimization in Planning and Operation of Electric Power Systems written by Karl Frauendorfer and published by Springer Science & Business Media. This book was released on 2013-10-14 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Permanently increasing requirements in power supply necessitate efficient control of electric power systems. An emerging subject of importance is optimization. Papers on modelling aspects of unit commitment and optimal power flow provide the introduction to power systems control and to its associated problem statement. Due to the nature of the underlying optimization problems recent developments in advanced and well established mathematical programming methodologies are presented, illustrating in which way dynamic, separable, continuous and stochastic features might be exploited. In completing the various methodologies a number of presentations have stated experiences with optimization packages currently used for unit commitment and optimal power flow calculations. This work represents a state-of-the-art of mathematical programming methodologies, unit commitment, optimal power flow and their applications in power system control.
Book Synopsis Stochastic Decomposition by : Julia L. Higle
Download or read book Stochastic Decomposition written by Julia L. Higle and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivation Stochastic Linear Programming with recourse represents one of the more widely applicable models for incorporating uncertainty within in which the SLP optimization models. There are several arenas model is appropriate, and such models have found applications in air line yield management, capacity planning, electric power generation planning, financial planning, logistics, telecommunications network planning, and many more. In some of these applications, modelers represent uncertainty in terms of only a few seenarios and formulate a large scale linear program which is then solved using LP software. However, there are many applications, such as the telecommunications planning problem discussed in this book, where a handful of seenarios do not capture variability well enough to provide a reasonable model of the actual decision-making problem. Problems of this type easily exceed the capabilities of LP software by several orders of magnitude. Their solution requires the use of algorithmic methods that exploit the structure of the SLP model in a manner that will accommodate large scale applications.
Book Synopsis The Basic George B. Dantzig by : George Bernard Dantzig
Download or read book The Basic George B. Dantzig written by George Bernard Dantzig and published by Stanford University Press. This book was released on 2003 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: The late George B. Dantzig , widely known as the father of linear programming, was a major influence in mathematics, operations research, and economics. As Professor Emeritus at Stanford University, he continued his decades of research on linear programming and related subjects. Dantzig was awarded eight honorary doctorates, the National Medal of Science, and the John von Neumann Theory Prize from the Institute for Operations Research and the Management Sciences. The 24 chapters of this volume highlight the amazing breadth and enduring influence of Dantzig's research. Short, non-technical summaries at the opening of each major section introduce a specific research area and discuss the current significance of Dantzig's work in that field. Among the topics covered are mathematical statistics, the Simplex Method of linear programming, economic modeling, network optimization, and nonlinear programming. The book also includes a complete bibliography of Dantzig's writings.
Book Synopsis Worldwide Asset and Liability Modeling by : William T. Ziemba
Download or read book Worldwide Asset and Liability Modeling written by William T. Ziemba and published by Cambridge University Press. This book was released on 1998-11-12 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: The underlying theme of this volume is how to invest assets over time to achieve satisfactory returns subject to uncertainties, various constraints and liability commitments. Most investors, be they individuals or institutions, do not diversify properly across markets nor across time. The papers utilize several approaches and integrate a number of techniques as well as discussing a variety of models that have either been implemented, are close to being implemented, or represent new innovative approaches that may lead to future novel applications. Other issues address the future of asset-liability management modeling. This includes models for individuals, and various financial institutions such as banks and insurance companies. This will lead to custom products, that is, financial engineering. All in all, this will be essential reading for all involved in analysing the financial markets.
Book Synopsis Stochastic Linear Programming by : Peter Kall
Download or read book Stochastic Linear Programming written by Peter Kall and published by Springer Science & Business Media. This book was released on 2005-07-25 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. Stochastic Linear Programming is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature.
Book Synopsis Stochastic Linear Programming Algorithms by : Janos Mayer
Download or read book Stochastic Linear Programming Algorithms written by Janos Mayer and published by Taylor & Francis. This book was released on 2022-04-19 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.
Book Synopsis Modeling with Stochastic Programming by : Alan J. King
Download or read book Modeling with Stochastic Programming written by Alan J. King and published by Springer Nature. This book was released on with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Stanford University. Department of Operations Research. Systems Optimization Laboratory Publisher : ISBN 13 : Total Pages :44 pages Book Rating :4.F/5 ( download)
Book Synopsis Solving Stochastic Linear Programs on a Hypercube Multicomputer by : Stanford University. Department of Operations Research. Systems Optimization Laboratory
Download or read book Solving Stochastic Linear Programs on a Hypercube Multicomputer written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1991 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of efficient importance sampling to stochastic volatility models by : Serda Selin Ozturk
Download or read book Applications of efficient importance sampling to stochastic volatility models written by Serda Selin Ozturk and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lectures on Stochastic Programming by : Alexander Shapiro
Download or read book Lectures on Stochastic Programming written by Alexander Shapiro and published by SIAM. This book was released on 2014-07-09 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Handbooks in Operations Research and Management Science by : K. Aardal
Download or read book Handbooks in Operations Research and Management Science written by K. Aardal and published by Elsevier. This book was released on 2005-12-08 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: The chapters of this Handbook volume cover nine main topics that are representative of recent theoretical and algorithmic developments in the field. In addition to the nine papers that present the state of the art, there is an article on the early history of the field. The handbook will be a useful reference to experts in the field as well as students and others who want to learn about discrete optimization.
Book Synopsis Handbook of Simulation Optimization by : Michael C Fu
Download or read book Handbook of Simulation Optimization written by Michael C Fu and published by Springer. This book was released on 2014-11-13 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology. Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners and graduate students in the business/engineering fields of operations research, management science, operations management and stochastic control, as well as in economics/finance and computer science.
