Encyclopedia of Operations Research and Management Science

2013 Edition
| Editors: Saul I. Gass, Michael C. Fu

Random Number Generators

  • Pierre L’Ecuyer
Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-1153-7_852


Many algorithms and heuristics in operations research and management science require a source of random numbers. This is needed in particular to simulate stochastic models, to estimate multivariate integrals and the solutions of differential equations numerically by Monte Carlo, and in probabilistic algorithms in general. These so-called random numbers are typically produced by a deterministic computer program, and are therefore not random at all. The program that produces them is nevertheless called a random number generator (RNG). Its aim is to imitate the realization of a sequence of i.i.d. (independent and identically distributed) random variables, say from the \( {\mathcal U} \)

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Département d'Informatique et de Recherche OpérationnelleUniversité de MontréalMontréalCanada