The integrity of computer simulation models is only as good as the reliability of the random number generator that produces the stream of random numbers one after the other. The chapter describes the difficult task of developing an algorithm to generate random numbers that are statistically valid and have a large cycle length. The linear congruent method is currently the common way to generate the random numbers for a computer. The parameters of this method include the multiplier and the seed. Only a few multipliers are statistically recommended, and two popular ones in use for 32-bit word length computers are presented. Another parameter is the seed and this allows the analyst the choice of altering the sequence of random numbers with each run, and also when necessary, offers the choice of using the same sequence of random numbers from one run to another.
CITATION STYLE
Thomopoulos, N. T. (2013). Random Number Generators. In Essentials of Monte Carlo Simulation (pp. 9–14). Springer New York. https://doi.org/10.1007/978-1-4614-6022-0_2
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