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Parallel Algorithms Of Continuous State And Control Stochastic Dynamic Programming Applied To Multi Reservoir Management
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Book Synopsis Parallel Algorithms of Continuous State and Control Stochastic Dynamic Programming Applied to Multi-reservoir Management by : Elizabeth Allen Eschenbach
Download or read book Parallel Algorithms of Continuous State and Control Stochastic Dynamic Programming Applied to Multi-reservoir Management written by Elizabeth Allen Eschenbach and published by . This book was released on 1994 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Markov Decision Processes by : Eugene A. Feinberg
Download or read book Handbook of Markov Decision Processes written by Eugene A. Feinberg and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a leading expert in the re spective area. The papers cover major research areas and methodologies, and discuss open questions and future research directions. The papers can be read independently, with the basic notation and concepts ofSection 1.2. Most chap ters should be accessible by graduate or advanced undergraduate students in fields of operations research, electrical engineering, and computer science. 1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems. The basic object is a discrete-time stochas tic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. The goal is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types ofimpacts: (i) they cost orsavetime, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view offuture events. MDPs model this paradigm and provide results on the structure and existence of good policies and on methods for their calculation.
Book Synopsis Water Policy and Management by : Darrell G. Fontane
Download or read book Water Policy and Management written by Darrell G. Fontane and published by . This book was released on 1994 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection contains 219 papers presented at the 21st Annual Conference on Water Resources Planning and Management, held in Denver, Colorado, May 23-26, 1994.
Book Synopsis Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2002 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Spring Meeting by : American Geophysical Union. Meeting
Download or read book Spring Meeting written by American Geophysical Union. Meeting and published by . This book was released on 1991 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistics in Industry by : Ravindra Khattree
Download or read book Statistics in Industry written by Ravindra Khattree and published by Gulf Professional Publishing. This book was released on 2003-07-18 with total page 1224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents an exposition of topics in industrial statistics. It serves as a reference for researchers in industrial statistics/industrial engineering and a source of information for practicing statisticians/industrial engineers. A variety of topics in the areas of industrial process monitoring, industrial experimentation, industrial modelling and data analysis are covered and are authored by leading researchers or practitioners in the particular specialized topic. Targeting the audiences of researchers in academia as well as practitioners and consultants in industry, the book provides comprehensive accounts of the relevant topics. In addition, whenever applicable ample data analytic illustrations are provided with the help of real world data.
Book Synopsis TIMS/ORSA Bulletin by : Institute of Management Sciences
Download or read book TIMS/ORSA Bulletin written by Institute of Management Sciences and published by . This book was released on 1993 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Approximate Dynamic Programming by : Warren B. Powell
Download or read book Approximate Dynamic Programming written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2007-10-05 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete and accessible introduction to the real-world applications of approximate dynamic programming With the growing levels of sophistication in modern-day operations, it is vital for practitioners to understand how to approach, model, and solve complex industrial problems. Approximate Dynamic Programming is a result of the author's decades of experience working in large industrial settings to develop practical and high-quality solutions to problems that involve making decisions in the presence of uncertainty. This groundbreaking book uniquely integrates four distinct disciplines—Markov design processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully model and solve a wide range of real-life problems using the techniques of approximate dynamic programming (ADP). The reader is introduced to the three curses of dimensionality that impact complex problems and is also shown how the post-decision state variable allows for the use of classical algorithmic strategies from operations research to treat complex stochastic optimization problems. Designed as an introduction and assuming no prior training in dynamic programming of any form, Approximate Dynamic Programming contains dozens of algorithms that are intended to serve as a starting point in the design of practical solutions for real problems. The book provides detailed coverage of implementation challenges including: modeling complex sequential decision processes under uncertainty, identifying robust policies, designing and estimating value function approximations, choosing effective stepsize rules, and resolving convergence issues. With a focus on modeling and algorithms in conjunction with the language of mainstream operations research, artificial intelligence, and control theory, Approximate Dynamic Programming: Models complex, high-dimensional problems in a natural and practical way, which draws on years of industrial projects Introduces and emphasizes the power of estimating a value function around the post-decision state, allowing solution algorithms to be broken down into three fundamental steps: classical simulation, classical optimization, and classical statistics Presents a thorough discussion of recursive estimation, including fundamental theory and a number of issues that arise in the development of practical algorithms Offers a variety of methods for approximating dynamic programs that have appeared in previous literature, but that have never been presented in the coherent format of a book Motivated by examples from modern-day operations research, Approximate Dynamic Programming is an accessible introduction to dynamic modeling and is also a valuable guide for the development of high-quality solutions to problems that exist in operations research and engineering. The clear and precise presentation of the material makes this an appropriate text for advanced undergraduate and beginning graduate courses, while also serving as a reference for researchers and practitioners. A companion Web site is available for readers, which includes additional exercises, solutions to exercises, and data sets to reinforce the book's main concepts.
Book Synopsis Models for Planning Under Uncertainty by : Hercules Vladimirou
Download or read book Models for Planning Under Uncertainty written by Hercules Vladimirou and published by . This book was released on 1995 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Programming Based Operation of Reservoirs by : K. D. W. Nandalal
Download or read book Dynamic Programming Based Operation of Reservoirs written by K. D. W. Nandalal and published by Cambridge University Press. This book was released on 2013-03-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic programming is a method of solving multi-stage problems in which decisions at one stage become the conditions governing the succeeding stages. It can be applied to the management of water reservoirs, allowing them to be operated more efficiently. This is one of the few books dedicated solely to dynamic programming techniques used in reservoir management. It presents the applicability of these techniques and their limits on the operational analysis of reservoir systems. The dynamic programming models presented in this book have been applied to reservoir systems all over the world, helping the reader to appreciate the applicability and limits of these models. The book also includes a model for the operation of a reservoir during an emergency situation. This volume will be a valuable reference to researchers in hydrology, water resources and engineering, as well as professionals in reservoir management.
Book Synopsis Reinforcement Learning and Stochastic Optimization by : Warren B. Powell
Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a “diary problem” that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.
Download or read book Documentation Abstracts written by and published by . This book was released on 1992 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Comprehensive Dissertation Index by :
Download or read book Comprehensive Dissertation Index written by and published by . This book was released on 1989 with total page 1116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Index to American Doctoral Dissertations by :
Download or read book Index to American Doctoral Dissertations written by and published by . This book was released on 1989 with total page 1252 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Water Resources Planning and Management by : Vijay Singh
Download or read book Water Resources Planning and Management written by Vijay Singh and published by Springer. This book was released on 1995-12-31 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water is vital to life, maintenance of ecological balance, economic development, and sustenance of civilization. Planning and management of water resources and its optimal use are a matter of urgency for most countries of the world, and even more so for India with a huge population. Growing population and expanding economic activities exert increasing demands on water for varied needs--domestic, industrial, agricultural, power generation, navigation, recreation, etc. In India, agriculture is the highest user of water. The past three decades have witnessed numerous advances as well as have presented intriguing challenges and exciting opportunities in hydrology and water resources. Compounding them has been the growing environmental consciousness. Nowhere are these challenges more apparent than in India. As we approach the twenty first century, it is entirely fitting to take stock of what has been accomplished and what remains to be accomplished, and what accomplishments are relevant, with particular reference to Indian conditions.
Download or read book The Engineering Index Annual written by and published by . This book was released on 1992 with total page 2264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its creation in 1884, Engineering Index has covered virtually every major engineering innovation from around the world. It serves as the historical record of virtually every major engineering innovation of the 20th century. Recent content is a vital resource for current awareness, new production information, technological forecasting and competitive intelligence. The world?s most comprehensive interdisciplinary engineering database, Engineering Index contains over 10.7 million records. Each year, over 500,000 new abstracts are added from over 5,000 scholarly journals, trade magazines, and conference proceedings. Coverage spans over 175 engineering disciplines from over 80 countries. Updated weekly.
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.
