© 2010

Applied Probability and Stochastic Processes


Table of contents

  1. Front Matter
    Pages i-xii
  2. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 1-43
  3. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 45-72
  4. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 73-113
  5. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 115-139
  6. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 141-179
  7. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 181-199
  8. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 201-225
  9. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 227-249
  10. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 251-284
  11. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 285-303
  12. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 305-321
  13. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 323-354
  14. Richard M. Feldman, Ciriaco Valdez-Flores
    Pages 355-379
  15. Back Matter
    Pages 1-17

About this book


This book presents applied probability and stochastic processes in an elementary but mathematically precise manner, with numerous examples and exercises to illustrate the range of engineering and science applications of the concepts. The book is designed to give the reader an intuitive understanding of probabilistic reasoning, in addition to an understanding of mathematical concepts and principles. The initial chapters present a summary of probability and statistics and then Poisson processes, Markov chains, Markov processes and queuing processes are introduced. Advanced topics include simulation, inventory theory, replacement theory, Markov decision theory, and the use of matrix geometric procedures in the analysis of queues.

Included in the second edition are appendices at the end of several chapters giving suggestions for the use of Excel in solving the problems of the chapter. Also new in this edition are an introductory chapter on statistics and a chapter on Poisson processes that includes some techniques used in risk assessment. The old chapter on queues has been expanded and broken into two new chapters: one for simple queuing processes and one for queuing networks. Support is provided through the web site where students will have the answers to odd numbered problems and instructors will have access to full solutions and Excel files for homework.


Inventory Theory Markov Chains Markov Decicision Processes Markov Processes Markov chain Markov decision process Markov process Monte Carlo Simulation Poisson Processes Poisson process Queueing Networks Queueing Processes Replacement Theory stochastic process

Authors and affiliations

  1. 1.Dept. Industrial & Systems EngineeringTexas A & M UniversityCollege StationUSA
  2. 2.Sielken & Associates Consulting, Inc.BryanUSA

About the authors

Richard M. Feldman is a Professor of Industrial and Systems Engineering at Texas A&M University. He received a B.A. degree in mathematics from Hope College, an M.S. degree in mathematics from Michigan State University, an M.S. degree in Industrial and Systems Engineering from Ohio University, and a Ph.D. in Industrial Engineering from Northwestern University. His teaching interests include simulation, applied probability, and queueing theory. His consulting and funded research activities have involved modeling and simulation within manufacturing, transportation, and biological contexts. He has received several teaching awards, published papers in applied probability and queueing theory, and co-authored four books.

Ciriaco Valdez-Flores is senior risk assessment consultant at Sielken & Associates Consulting, Inc. He received a bachelor’s degree from the Tecnológico at Cd. Victoria in México and master’s and Ph.D. degrees from Texas A&M University, all in Industrial Engineering. He has taught graduate courses at Texas A&M University focusing in the areas of operations research and applied stochastic processes. As a consultant, he applies his background to the development of new methods of quantitative health risk assessment that incorporate simulation and decision tree theory. He has published in health risk assessment and stochastic processes, co-authored one book and has contributed to books in engineering economy and risk assessment.

Bibliographic information

Industry Sectors
Chemical Manufacturing
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences


amazon.con Customer Reviews on 1st edition:

5.0 out of 5 stars It's worth at least six stars!, February 19, 2000
By Lisa Ann Ball (Seattle, WA United States) - See all my reviews

I randomly ran across this book in my math library trying to find an extra book to help with the difficult Stochastics Process class I was taking. Little did I know I would find a book I value as much as Douglas Kelly's Introduction to Probability. This book has applied problems and examples! It is not the dry, endless pages of confusing equations we have come to expect from Stochastics Processes books. There is something better out there! This book saved me as an undergraduate, and am now looking forward to it living up to my God like expectations as a post grad. If you are a professor, please use this book for you students. It ties together and lets you appreciate many fields such as linear analysis and even graph theory from computer science. This book will not disappoint.

5.0 out of 5 stars Best introductory book, February 22, 2001
By Brad (Austin, TX USA) - See all my reviews

Extremely clear, and easy to understand. It is the best introductory book on stochastic processes for non-mathematics major. After you read this book (one month is enough, how amazing it is!), it becomes easier to read "the first course in stochastic processes". The book focuses on the concept and intuition, instead of proof, and I find it is extremely useful for me -- CS major.
Strong recommend this great book

5.0 out of 5 stars Good book! , August 13, 2007
By Yuan J. Son (sunnyvale, CA) - See all my reviews
A lot of examples, easy to read. A lot of stochastic and queuing books are usually full of notations and theorems, thus hard to understand. However, the author of this book presented the materials in a way that we can actually understand the stochastic processes. If you want to learn queuing and do not have much background, this is the book!!!!