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SSJ is a Java library for stochastic simulation, developed under the direction of Pierre L'Ecuyer,
in the Département d'Informatique et de Recherche Opérationnelle (DIRO), at the Université de Montréal.
It provides facilities for generating uniform and nonuniform random variates, computing different
measures related to probability distributions, performing goodness-of-fit tests, applying quasi-Monte
Carlo methods, collecting (elementary) statistics, and programming discrete-event simulations with both
events and processes.
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import umontreal.iro.lecuyer.stat.*;
import umontreal.iro.lecuyer.rng.*;
import umontreal.iro.lecuyer.probdist.ExponentialDist;
import umontreal.iro.lecuyer.util.Chrono;
public class QueueLindley {
RandomStream streamArr = new MRG32k3a();
RandomStream streamServ = new MRG32k3a();
Tally averageWaits = new Tally ("Average waits");
public double simulateOneRun (int numCust, double lambda, double mu) {
double Wi = 0.0;
double sumWi = 0.0;
for (int i = 2; i <= numCust; i++) {
Wi += ExponentialDist.inverseF (mu, streamServ.nextDouble()) -
ExponentialDist.inverseF (lambda, streamArr.nextDouble());
if (Wi < 0.0) Wi = 0.0;
sumWi += Wi;
}
return sumWi / numCust;
}
public void simulateRuns (int n, int numCust, double lambda, double mu) {
averageWaits.init();
for (int i=0; i