Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor and published by Academic Press. This book was released on 2014-05-10 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Download or read book Introduction to Stochastic Models in Operations Research written by Frederick S. Hillier and published by . This book was released on 1990 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Models in Operations Research written by Daniel P. Heyman and published by Courier Corporation. This book was released on 2004-01-01 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of a 2-volume set explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. Explores stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, this graduate-level text emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models.

Download or read book Introduction to Modeling and Analysis of Stochastic Systems written by V. G. Kulkarni and published by Springer. This book was released on 2010-11-03 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a self-contained review of all the relevant topics in probability theory. A software package called MAXIM, which runs on MATLAB, is made available for downloading. Vidyadhar G. Kulkarni is Professor of Operations Research at the University of North Carolina at Chapel Hill.

Download or read book Stochastic Models in Operations Research Stochastic optimization written by Daniel P. Heyman and published by Courier Corporation. This book was released on 2004-01-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate treatments: stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, they emphasize the practical importance, intellectual stimulation, and mathematical elegance of stochastic models and are intended primarily as graduate-level texts.

Download or read book Introduction to Stochastic Models in Operations Research written by İlhan Or and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stochastic Processes and Models in Operations Research written by Anbazhagan, Neelamegam and published by IGI Global. This book was released on 2016-03-24 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision-making is an important task no matter the industry. Operations research, as a discipline, helps alleviate decision-making problems through the extraction of reliable information related to the task at hand in order to come to a viable solution. Integrating stochastic processes into operations research and management can further aid in the decision-making process for industrial and management problems. Stochastic Processes and Models in Operations Research emphasizes mathematical tools and equations relevant for solving complex problems within business and industrial settings. This research-based publication aims to assist scholars, researchers, operations managers, and graduate-level students by providing comprehensive exposure to the concepts, trends, and technologies relevant to stochastic process modeling to solve operations research problems.

Download or read book Operations Research Introduction To Models And Methods written by Richard Johannes Boucherie and published by World Scientific. This book was released on 2021-10-26 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book An Introduction to Stochastic Modeling written by Howard M. Taylor and published by Academic Press. This book was released on 2014-05-10 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Stochastic Modeling, Revised Edition provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.

Download or read book Optimization of Stochastic Models written by Georg Ch. Pflug and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic models are everywhere. In manufacturing, queuing models are used for modeling production processes, realistic inventory models are stochastic in nature. Stochastic models are considered in transportation and communication. Marketing models use stochastic descriptions of the demands and buyer's behaviors. In finance, market prices and exchange rates are assumed to be certain stochastic processes, and insurance claims appear at random times with random amounts. To each decision problem, a cost function is associated. Costs may be direct or indirect, like loss of time, quality deterioration, loss in production or dissatisfaction of customers. In decision making under uncertainty, the goal is to minimize the expected costs. However, in practically all realistic models, the calculation of the expected costs is impossible due to the model complexity. Simulation is the only practicable way of getting insight into such models. Thus, the problem of optimal decisions can be seen as getting simulation and optimization effectively combined. The field is quite new and yet the number of publications is enormous. This book does not even try to touch all work done in this area. Instead, many concepts are presented and treated with mathematical rigor and necessary conditions for the correctness of various approaches are stated. Optimization of Stochastic Models: The Interface Between Simulation and Optimization is suitable as a text for a graduate level course on Stochastic Models or as a secondary text for a graduate level course in Operations Research.

Download or read book Selected Topics On Stochastic Modelling written by Mariano J Valderrama Bonnet and published by World Scientific. This book was released on 1994-09-30 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a selection of papers on recent developments in fields such as stochastic processes, multivariate data analysis and stochastic models in operations research, earth and life sciences and information theory, from an applicative perspective. Some of them have been extracted from lectures given at the Department of Statistics and Operations Research at the University of Granada for the past two years (Kai Lai Chung and Marcel F Neuts, among others). All the papers have been carefully selected and revised.

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.

Download or read book Stochastic Models with Power Law Tails written by Dariusz Buraczewski and published by Springer. This book was released on 2016-07-04 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this monograph the authors give a systematic approach to the probabilistic properties of the fixed point equation X=AX+B. A probabilistic study of the stochastic recurrence equation X_t=A_tX_{t-1}+B_t for real- and matrix-valued random variables A_t, where (A_t,B_t) constitute an iid sequence, is provided. The classical theory for these equations, including the existence and uniqueness of a stationary solution, the tail behavior with special emphasis on power law behavior, moments and support, is presented. The authors collect recent asymptotic results on extremes, point processes, partial sums (central limit theory with special emphasis on infinite variance stable limit theory), large deviations, in the univariate and multivariate cases, and they further touch on the related topics of smoothing transforms, regularly varying sequences and random iterative systems. The text gives an introduction to the Kesten-Goldie theory for stochastic recurrence equations of the type X_t=A_tX_{t-1}+B_t. It provides the classical results of Kesten, Goldie, Guivarc'h, and others, and gives an overview of recent results on the topic. It presents the state-of-the-art results in the field of affine stochastic recurrence equations and shows relations with non-affine recursions and multivariate regular variation.

Download or read book Stochastic Modeling and Optimization written by David D. Yao and published by Springer Science & Business Media. This book was released on 2003-01-14 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

Download or read book Stochastic Models in Operations Research written by Daniel P. Heyman and published by . This book was released on 2000 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modeling with Stochastic Programming written by Alan J. King and published by Springer Science & Business Media. This book was released on 2012-06-19 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research at Lancaster University Management School in England.

Download or read book Stochastic Models written by Daniel P. Heyman and published by North Holland. This book was released on 1990-01-01 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the central problems in operations research and management science is how to quantify the effects of uncertainty about the future. This, the second volume in a series of handbooks, is devoted to models where chance events play a major role. The thirteen chapters survey topics in applied probability that have been particularly useful in operations research and management science. Each chapter was written by an expert, both in subject matter and in its exposition. The chapters fall into four groups. The first four cover the fundamentals of stochastic processes, and lay the foundation for the following chapters. The next three chapters are concerned with methods of getting numbers. This includes numerical solution of models, parameter estimation for models, and simulation of models. Chapters 8 and 9 describe the fundamentals of dynamic optimization. The last four chapters are concerned with the most important structured models in operations research and management science; queues, queueing networks, inventories, and reliability.