Introduction To Stochastic Dynamic Programming
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Introduction To Stochastic Dynamic Programming
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Author : Sheldon M. Ross
language : en
Publisher: Elsevier
Release Date : 1995-08-24
Introduction To Stochastic Dynamic Programming written by Sheldon M. Ross and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-08-24 with Mathematics categories.
Introduction to Stochastic Dynamic Programming
Introduction To Stochastic Programming
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Author : John R. Birge
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-15
Introduction To Stochastic Programming written by John R. Birge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-15 with Business & Economics categories.
The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now 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 aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on 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. In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods. The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition: "The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make 'Introduction to Stochastic Programming' an ideal textbook for the area." (Interfaces, 1998)
Introduction To Stochastic Programming
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Author : John R. Birge
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-06
Introduction To Stochastic Programming written by John R. Birge and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-06 with Mathematics categories.
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.
An Introduction To Deterministic And Stochastic Dynamic Programming
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Author : Norman J. Dudley
language : en
Publisher:
Release Date : 1998
An Introduction To Deterministic And Stochastic Dynamic Programming written by Norman J. Dudley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Dynamic programming categories.
Operations Research Introduction To Models And Methods
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Author : Richard Johannes Boucherie
language : en
Publisher: World Scientific
Release Date : 2021-10-26
Operations Research Introduction To Models And Methods written by Richard Johannes Boucherie and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-26 with Mathematics categories.
This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.
Applied Stochastic Models And Control For Finance And Insurance
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Author : Charles S. Tapiero
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Applied Stochastic Models And Control For Finance And Insurance written by Charles S. Tapiero and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
Applied Stochastic Models and Control for Finance and Insurance presents at an introductory level some essential stochastic models applied in economics, finance and insurance. Markov chains, random walks, stochastic differential equations and other stochastic processes are used throughout the book and systematically applied to economic and financial applications. In addition, a dynamic programming framework is used to deal with some basic optimization problems. The book begins by introducing problems of economics, finance and insurance which involve time, uncertainty and risk. A number of cases are treated in detail, spanning risk management, volatility, memory, the time structure of preferences, interest rates and yields, etc. The second and third chapters provide an introduction to stochastic models and their application. Stochastic differential equations and stochastic calculus are presented in an intuitive manner, and numerous applications and exercises are used to facilitate their understanding and their use in Chapter 3. A number of other processes which are increasingly used in finance and insurance are introduced in Chapter 4. In the fifth chapter, ARCH and GARCH models are presented and their application to modeling volatility is emphasized. An outline of decision-making procedures is presented in Chapter 6. Furthermore, we also introduce the essentials of stochastic dynamic programming and control, and provide first steps for the student who seeks to apply these techniques. Finally, in Chapter 7, numerical techniques and approximations to stochastic processes are examined. This book can be used in business, economics, financial engineering and decision sciences schools for second year Master's students, as well as in a number of courses widely given in departments of statistics, systems and decision sciences.
Computational Finance 1999
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Author : Yaser S. Abu-Mostafa
language : en
Publisher: MIT Press
Release Date : 2000
Computational Finance 1999 written by Yaser S. Abu-Mostafa and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Business & Economics categories.
This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. Computational finance, an exciting new cross-disciplinary research area, draws extensively on the tools and techniques of computer science, statistics, information systems, and financial economics. This book covers the techniques of data mining, knowledge discovery, genetic algorithms, neural networks, bootstrapping, machine learning, and Monte Carlo simulation. These methods are applied to a wide range of problems in finance, including risk management, asset allocation, style analysis, dynamic trading and hedging, forecasting, and option pricing. The book is based on the sixth annual international conference Computational Finance 1999, held at New York University's Stern School of Business.
Introduction To Modern Economic Growth
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Author : Daron Acemoglu
language : en
Publisher: Princeton University Press
Release Date : 2008-12-15
Introduction To Modern Economic Growth written by Daron Acemoglu and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-15 with Business & Economics categories.
From Nobel Prize–winning economist Daron Acemoglu, an incisive introduction to economic growth Introduction to Modern Economic Growth is a groundbreaking text from one of today's leading economists. Daron Acemoglu gives graduate students not only the tools to analyze growth and related macroeconomic problems, but also the broad perspective needed to apply those tools to the big-picture questions of growth and divergence. And he introduces the economic and mathematical foundations of modern growth theory and macroeconomics in a rigorous but easy to follow manner. After covering the necessary background on dynamic general equilibrium and dynamic optimization, the book presents the basic workhorse models of growth and takes students to the frontier areas of growth theory, including models of human capital, endogenous technological change, technology transfer, international trade, economic development, and political economy. The book integrates these theories with data and shows how theoretical approaches can lead to better perspectives on the fundamental causes of economic growth and the wealth of nations. Innovative and authoritative, this book is likely to shape how economic growth is taught and learned for years to come. Introduces all the foundations for understanding economic growth and dynamic macroeconomic analysis Focuses on the big-picture questions of economic growth Provides mathematical foundations Presents dynamic general equilibrium Covers models such as basic Solow, neoclassical growth, and overlapping generations, as well as models of endogenous technology and international linkages Addresses frontier research areas such as international linkages, international trade, political economy, and economic development and structural change An accompanying Student Solutions Manual containing the answers to selected exercises is available (978-0-691-14163-3/$24.95). See: https://press.princeton.edu/titles/8970.html For Professors only: To access a complete solutions manual online, email us at: [email protected]
Introduction To Probability Models
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Author : Wayne L. Winston
language : en
Publisher: Duxbury Resource Center
Release Date : 2004
Introduction To Probability Models written by Wayne L. Winston and has been published by Duxbury Resource Center this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
Vol. 2: CD-ROM contains student editions of: ProcessModel, LINGO, Premium Solver, DecisionTools Suite including @RISK AND RISKOptimizer, Data files.
Dynamic Programming Based Operation Of Reservoirs
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Author : K. D. W. Nandalal
language : en
Publisher: Cambridge University Press
Release Date : 2007-05-10
Dynamic Programming Based Operation Of Reservoirs written by K. D. W. Nandalal and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-10 with Science categories.
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.