COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
Regenerative Stochastic Simulation - 1st Edition - ISBN: 9780126393606, 9780080925721

Regenerative Stochastic Simulation

1st Edition

Author: Gerald Shedler
Hardcover ISBN: 9780126393606
eBook ISBN: 9780080925721
Imprint: Academic Press
Published Date: 17th December 1992
Page Count: 400
Sales tax will be calculated at check-out Price includes VAT/GST
Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.


Simulation is a controlled statistical sampling technique that can be used to study complex stochastic systems when analytic and/or numerical techniques do not suffice. The focus of this book is on simulations of discrete-event stochastic systems; namely, simulations in which stochastic state transitions occur only at an increasing sequence of random times. The discussion emphasizes simulations on a finite or countably infinite state space.

Key Features

  • Develops probabilistic methods for simulation of discrete-event stochastic systems
  • Emphasizes stochastic modeling and estimation procedures based on limit theorems for regenerative stochastic processes
  • Includes engineering applications of discrete-even simulation to computer, communication, manufacturing, and transportation systems
  • Focuses on simulations with an underlying stochastic process that can specified as a generalized semi-Markov process
  • Unique approach to simulation, with heavy emphasis on stochastic modeling
  • Includes engineering applications for computer, communication, manufacturing, and transportation systems


The presentation is self contained. Some knowledge of elementary probability theory, statistics, and stochastic models is necessary for an understanding of the theory and the examples. Many of the arguments use results often contained in a first year graduate course on stochastic process. A brief review of the necessary material is in Appendix A.

Table of Contents

Preface. Discrete-Event Simulations. Regenerative Stochastic Processes. Regenerative Simulation. Networks of Queues. Passage Times. Simulations With Simultaneous Events. Appendix A. Limit Theorems for Stochastic Processes. Appendix B. Random Number Generation.


No. of pages:
© Academic Press 1993
17th December 1992
Academic Press
Hardcover ISBN:
eBook ISBN:

About the Author

Gerald Shedler

Affiliations and Expertise

IBM Research Divison

Ratings and Reviews