SIMSCRIPT II.5 Programming Language

Discrete Simulation Concepts
1. if random.f(1) less than TRANSITION.PROBABILITY
let COUNT = COUNT + 1
always
2. for each CONTESTANT,
do
if random.f(CONTESTANT) greater than FINISH,
file CONTESTANT in POSSIBLE.WINNER
always
add 1 to STEPS(CONTESTANTS)
loop
Random.f can be viewed in two ways — as generating uniformly distributed pseudorandom variables
between 0 and 1 or as generating probabilities. The above examples illustrate the use of the
function in the probability sense.
SIMSCRIPT II.5 provides twelve functions for generating independent, pseudorandom samples
from commonly encountered statistical distributions. Each of these functions has as its arguments
the parameters that describe the distribution and a pseudorandom number stream index. Each time
one of these functions is invoked, one or more pseudorandom numbers are generated from the indicated
stream, using random.f, and an appropriate transformation is made to produce the correct
sampling distribution. The functions, the arguments, and their properties are described in table 5-5.
If the stream number, i, is negative in any of these function calls, a quantity called an antithetic variate,
1 - random.f(abs.f(i)), is generated. Antithetic variates are used in simulation experiments
to reduce the variance of estimates of simulation-generated data. Discussions of their use can
be found in most simulation texts.
These statistical functions are often used with simulation models to generate event times and activity
durations. Some examples illustrate their use.
1. An activity generator process schedules task processes, assuming that the time between
successive task initiations is an exponentially distributed quantity with mean time of MEAN
days. For example:
process GENERATOR
until time.v gt TIME.LIMIT
do
activate a TASK now
wait exponential.f(MEAN, 1) days
loop
return
end
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