© 1999

Modeling, Analysis, Design, and Control of Stochastic Systems


Part of the Springer Text in Statistics book series (STS)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. V.G. Kulkarni
    Pages 1-25
  3. V.G. Kulkarni
    Pages 27-63
  4. V.G. Kulkarni
    Pages 65-85
  5. V.G. Kulkarni
    Pages 87-103
  6. V.G. Kulkarni
    Pages 105-152
  7. V.G. Kulkarni
    Pages 153-213
  8. V.G. Kulkarni
    Pages 215-250
  9. V.G. Kulkarni
    Pages 251-300
  10. V.G. Kulkarni
    Pages 301-316
  11. V.G. Kulkarni
    Pages 317-351
  12. Back Matter
    Pages 353-375

About this book


This is an introductory level text on stochastic modeling. It is suited for undergraduate or graduate students in actuarial science, business management, computer science, engineering, operations research, public policy, statistics, and mathematics. It employs a large number of examples to teach how to build stochastic models of physical systems, analyze these models to predict their performance, and use the analysis to design and control them. The book provides a self-contained review of the relevant topics in probability theory. The rest of the book is devoted to important classes of stochastic models. In discrete and continuous time Markov models it covers the transient and long term behavior, cost models, and first passage times. Under generalized Markov models, it covers renewal processes, cumulative processes and semi-Markov processes. All the material is illustrated with many examples. There is a separate chapter on queueing models. In the chapter on design the author shows how the techniques developed in the text can be used to optimize the performance of a system. Finally, in the last chapter, linear programming is used to compute optimal control policies for stochastic systems. The book emphasizes numerical answers to the problems. 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 Craolina at Chapel Hill. He has authored a graduate level text 'Modeling and Analysis of Stochastic Systems' and research articles on stochastic models of queues, computer systems and telecommunication systems. He holds a patent on traffic management in telecommunication networks, and he has served as an editor and associate editor of Stochastic Models and Operations Research Letters.


MATLAB Markov Markov model Markov process Probability theory Random variable Sage Stochastic model Stochastic modelling Stochastic models communication linear optimization modelling operations research programming

Authors and affiliations

  1. 1.Department of Operations ResearchUniversity of North CarolinaChapel HillUSA

Bibliographic information

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