7. Discrete Event Simulation

  1. Dirk P. Kroese1,
  2. Thomas Taimre1 and
  3. Zdravko I. Botev2

Published Online: 20 SEP 2011

DOI: 10.1002/9781118014967.ch7

Handbook of Monte Carlo Methods

Handbook of Monte Carlo Methods

How to Cite

Kroese, D. P., Taimre, T. and Botev, Z. I. (2011) Discrete Event Simulation, in Handbook of Monte Carlo Methods, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118014967.ch7

Author Information

  1. 1

    University of Queensland

  2. 2

    Université de Montréal

Publication History

  1. Published Online: 20 SEP 2011
  2. Published Print: 28 FEB 2011

ISBN Information

Print ISBN: 9780470177938

Online ISBN: 9781118014967

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Keywords:

  • discrete event simulation;
  • event-oriented simulation;
  • Monte Carlo simulation

Summary

Monte Carlo simulation generally involves simple algorithms for computing numerical quantities (expectations, probabilities) that are formulated in terms of basic random objects. In this respect Monte Carlo simulation differs from large-scale simulation modeling, in which the objective is to understand the workings of a real-life system by imitating it as well as possible on a computer. The purpose of this chapter is to provide a brief introduction to the most common aspects of computer simulation and modeling, in particular with regard to discrete event systems. Discrete event systems can be readily simulated on a computer by specifying precisely when events occur and how they affect the system state. There are two fundamental approaches to implementing a discrete event simulation program: event-oriented approach, and process-oriented approach. The chapter focuses on event-oriented simulation, which is generally easier to implement in a general-purpose programming language.

Controlled Vocabulary Terms

Monte Carlo methods; statistical data