Batch Mode Simulation : The Simulation Control Program : Random Functions : List of Random Functions

List of Random Functions
RANDOM - accepts an integer argument i and returns random real value distributed uniformly between 0 and 1. If the passed argument is not zero, then a new sequence of random values, whose seed is the parameter i, is initialized.

Syntax: random(i)

Since the Simulation tool always initiates a session with the same seed for random functions, two consecutive executions behave identically. The advantage is that you can reconstruct a particular execution scenario. New scenarios are produced by providing different seeds.
RAND_EXPONENTIAL - accepts a real argument and returns random real values distributed exponentially by the value t. Using the syntax x:=rand_exponential(t) make x equal to a randomly generated number. The syntax x:=random_exponential(t) is accepted, but it makes x=the first value in an array called random_exponential.

Function: X ~ exp(t)
Syntax: random_exponential(t)
RAND_BINOMIAL - accepts two arguments n and p, where n>0 and 0<p<1. The returned random values are real number distributed according to a binomial distribution.

Function: X ~ B(n,p)
Syntax: rand_binomial(n,p)
RAND_POISSON - accepts a real argument r. The returned random values are integers distributed according to a poisson distribution.

Function: X ~ P(r)
Syntax: rand_poisson(r)
RAND_UNIFORM - accepts two real arguments a and b. The returned random values are real values distributed according to a uniform distribution in the interval [a,b].

Function: X ~ U[a,b]
Syntax: rand_uniform(a,b)
RAND_IUNIFORM - same as rand_uniform except that a and b are integers and the value returned is an integer in the interval [a,b].

Function: X ~ U[a,b]
Syntax: rand_iuniform(a,b)
RAND_NORMAL - accepts two real arguments a and b. The returned random values are real values distributed according to a normal distribution.

Function: X ~ N[a,b]
Syntax: rand_normal(a,b)