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Scenario Reduction In Stochastic Programming
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Book Synopsis Scenario Reduction in Stochastic Programming by : Jitka Dupačová
Download or read book Scenario Reduction in Stochastic Programming written by Jitka Dupačová and published by . This book was released on 2000 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Problem-based Optimal Scenario Generation and Reduction in Stochastic Programming by : René Henrion
Download or read book Problem-based Optimal Scenario Generation and Reduction in Stochastic Programming written by René Henrion and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Scenarios are indispensable ingredients for the numerical solution of stochastic programs. Earlier approaches to optimal scenario generation and reduction are based on stability arguments involving distances of probability measures. In this paper we review those ideas and suggest to make use of stability estimates based only on problem specific data. For linear two-stage stochastic programs we show that the problem-based approach to optimal scenario generation can be reformulated as best approximation problem for the expected recourse function which in turn can be rewritten as a generalized semi-infinite program. We show that the latter is convex if either right-hand sides or costs are random and can be transformed into a semi-infinite program in a number of cases. We also consider problem-based optimal scenario reduction for two-stage models and optimal scenario generation for chance constrained programs. Finally, we discuss problem-based scenario generation for the classical newsvendor problem.
Book Synopsis Scenario Reduction in Stochastic Programming by : Jitka Dupačová
Download or read book Scenario Reduction in Stochastic Programming written by Jitka Dupačová and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scenario Reduction in Stochastic Programming with Respect to Discrepancy Distances by : René Henrion
Download or read book Scenario Reduction in Stochastic Programming with Respect to Discrepancy Distances written by René Henrion and published by . This book was released on 2006 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Technological Innovation for Life Improvement by : Luis M. Camarinha-Matos
Download or read book Technological Innovation for Life Improvement written by Luis M. Camarinha-Matos and published by Springer Nature. This book was released on 2020-04-29 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, held in Costa de Caparica, Portugal, in July 2020. The 20 full papers and 24 short papers presented were carefully reviewed and selected from 91 submissions. The papers present selected results produced in engineering doctoral programs and focus on technological innovation for industry and service systems. Research results and ongoing work are presented, illustrated and discussed in the following areas: collaborative networks; decisions systems; analysis and synthesis algorithms; communication systems; optimization systems; digital twins and smart manufacturing; power systems; energy control; power transportation; biomedical analysis and diagnosis; and instrumentation in health.
Book Synopsis Multistage Stochastic Optimization by : Georg Ch. Pflug
Download or read book Multistage Stochastic Optimization written by Georg Ch. Pflug and published by Springer. This book was released on 2014-11-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Applications of Stochastic Programming by : Stein W. Wallace
Download or read book Applications of Stochastic Programming written by Stein W. Wallace and published by SIAM. This book was released on 2005-01-01 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
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 2009-01-01 with total page 447 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. Readers will find coverage of the basic concepts of modeling these problems, including recourse actions and the nonanticipativity principle. The book also includes the theory of two-stage and multistage stochastic programming problems; the current state of the theory on chance (probabilistic) constraints, including the structure of the problems, optimality theory, and duality; and statistical inference in and risk-averse approaches to stochastic programming.
Book Synopsis Scenario Reduction Algorithms in Stochastic Programming by : Holger Heitsch
Download or read book Scenario Reduction Algorithms in Stochastic Programming written by Holger Heitsch and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mass Transportation Problems by : Svetlozar T. Rachev
Download or read book Mass Transportation Problems written by Svetlozar T. Rachev and published by Springer Science & Business Media. This book was released on 2006-05-17 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive account of the theory of mass transportation problems and its applications. In Volume I, the authors systematically develop the theory with emphasis on the Monge-Kantorovich mass transportation and the Kantorovich-Rubinstein mass transshipment problems. They then discuss a variety of different approaches towards solving these problems and exploit the rich interrelations to several mathematical sciences - from functional analysis to probability theory and mathematical economics. The second volume is devoted to applications of the above problems to topics in applied probability, theory of moments and distributions with given marginals, queuing theory, risk theory of probability metrics and its applications to various fields, among them general limit theorems for Gaussian and non-Gaussian limiting laws, stochastic differential equations and algorithms, and rounding problems. Useful to graduates and researchers in theoretical and applied probability, operations research, computer science, and mathematical economics, the prerequisites for this book are graduate level probability theory and real and functional analysis.
Book Synopsis Optimal Scenario Generation and Reduction in Stochastic Programming by : René Henrion
Download or read book Optimal Scenario Generation and Reduction in Stochastic Programming written by René Henrion and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 Probability Metrics and the Stability of Stochastic Models by : Svetlozar T. Rachev
Download or read book Probability Metrics and the Stability of Stochastic Models written by Svetlozar T. Rachev and published by . This book was released on 1991-05-13 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentrates on four specialized research directions as well as applications to different problems of probability theory. These include: description of the basic structure of p. metrics, analysis of the topologies in the space of probability measures generated by different types of p. metrics, characterization of the ideal metrics for the given problem and investigations of the main relationships between different types of p. metrics. The presentation here is given in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases.
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 Introduction to Stochastic Programming by : John R. Birge
Download or read book Introduction to Stochastic Programming written by John R. Birge and published by Springer Science & Business Media. This book was released on 2006-04-06 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This rapidly developing field encompasses many disciplines including operations research, mathematics, and probability. Conversely, it is being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors present a broad overview of the main themes and methods of the subject, thus helping students develop an intuition for how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. The early chapters introduce some worked examples of stochastic programming, demonstrate how a stochastic model is formally built, develop the properties of stochastic programs and the basic solution techniques used to solve them. The book then goes on to cover approximation and sampling techniques and is rounded off by an in-depth case study. A well-paced and wide-ranging introduction to this subject.
Book Synopsis Scenario Reduction Heuristics for a Rolling Stochastic Programming Simulation of Bulk Energy Flows with Uncertain Fuel Costs by : Yan Wang
Download or read book Scenario Reduction Heuristics for a Rolling Stochastic Programming Simulation of Bulk Energy Flows with Uncertain Fuel Costs written by Yan Wang and published by . This book was released on 2010 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: