Download or read book Response Surface Analysis of Two stage Stochastic Linear Programming with Recourse written by Thomas Glenn Bailey and published by . This book was released on 1995 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Response surface analysis of two stage stochastic linear programming with recourse written by Thomas Glenn Bailey and published by . This book was released on 1995 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Two Stage Stochastic Linear Programming with Recourse written by David Mills and published by . This book was released on 1999-03-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: The LP recourse problem applies to two-stage optimization problems where uncertainty in resource availability of the second stage hinders informed decision making. The recourse function affords a way to compensate "later" for an error in prediction "now." The literature provides a rich body of work on the optimization of such problems, but little research has been accomplished regarding the characterization of the surface in the local region of optimality, in particular sensitivity analysis. A decision maker faced with considerations other than the modeled objective function must be presented with a way to estimate the impact of operating at non-optimal decision variable values. This work develops and demonstrates a technique for characterizing the surface using response surface methodology. Specifically, the flexibility and utility of RSM techniques applied to this class of problems is demonstrated, and a methodology for characterizing the surface in the local region using a low-order polynomial is developed.
Download or read book Stochastic Linear Programming written by Peter Kall and published by Springer Science & Business Media. This book was released on 2005 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: CONTENIDO: Basic - Linear Programming Prerequisites - Nonlinear Programming Prerequisites - Single-Stage SLP models - Models involving probability functions - Quantile functions, Value at Risk - Models based on expectation - Models built with deviation measures - Modeling risk and opportunity - Risk measures - Multi-stage SLP models - The general SLP with recourse - The two-stage SLP - The multi-stage SLP - Algorithms - Single-stage models with separate probability functions - Single-stage models with joint probability functions - Single-stage models based on expectation - Single-stage models involving VaR - Single-stage models with deviation measures - Two-stage recourse models - Multistage recourse models - Modeling systems for SLP.
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.
Download or read book Applications of Stochastic Programming written by Stein W. Wallace and published by SIAM. This book was released on 2005-06-01 with total page 701 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.
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.?
Download or read book Lectures on Stochastic Programming Modeling and Theory Third Edition written by Alexander Shapiro and published by SIAM. This book was released on 2021-08-19 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible and rigorous presentation of contemporary models and ideas of stochastic programming, this book focuses on optimization problems involving uncertain parameters for which stochastic models are available. Since these problems occur in vast, diverse areas of science and engineering, there is much interest in rigorous ways of formulating, analyzing, and solving them. This substantially revised edition presents a modern theory of stochastic programming, including expanded and detailed coverage of sample complexity, risk measures, and distributionally robust optimization. It adds two new chapters that provide readers with a solid understanding of emerging topics; updates Chapter 6 to now include a detailed discussion of the interchangeability principle for risk measures; and presents new material on formulation and numerical approaches to solving periodical multistage stochastic programs. Lectures on Stochastic Programming: Modeling and Theory, Third Edition is written for researchers and graduate students working on theory and applications of optimization, with the hope that it will encourage them to apply stochastic programming models and undertake further studies of this fascinating and rapidly developing area.
Download or read book Stochastic Programming written by Gerd Infanger and published by Springer Science & Business Media. This book was released on 2010-11-10 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Optimization of Stochastic Response Surfaces Subject to Constraints with Linear Programming written by and published by . This book was released on 1992 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research investigated an alternative to the traditional approaches of optimizing a stochastic response surface subject to constraints. This research investigated the bias in the expected value of the solution, possible alternative decision variable settings, and a method to improve the solution. A three step process is presented to evaluate stochastic response surfaces subject to constraints. Step 1 is to use a traditional approach to estimate the response surface and a covariance matrix through regression. Step 2 samples the objective function of the linear program (i.e., response surface) and identifies the extreme points visited. Step 3 presents a method to estimate the optimal extreme point and present that information to a decision maker.
Download or read book Encyclopedia of Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2008-09-04 with total page 4646 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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".
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.
Download or read book A Reduced Gradient Based Procedure for Two stage Stochastic Linear Programming written by Alexander E. Pound and published by . This book was released on 2000 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Naval Research Logistics written by and published by . This book was released on 1987 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Programming Methods in the Response Surface Methodology written by José A. Díaz-García and published by . This book was released on 2018 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Considering the minimization of an estimated second degree response surface model as a problem of stochastic programming, this article establishes the equivalent deterministic programs applying the E-model, V-model, P-model and minimax methods. Similarly, after observing that some of the solutions by the techniques of stochastic programming coincide with the solution of a multiobjective optimization problem, we propose two alternative methods for the solution of the stochastic optimization of a second degree response surface model: The lexicographic method and the method based on distances. We end by solving an example by means of the described techniques.
Download or read book A QUADRATIC RECOURSE FUNCTION FOR THE TWO STAGE STOCHASTIC PROGRAM written by JOHN R. BIRGE, STEPHEN M. POLLACK and published by . This book was released on with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
