umontreal.iro.lecuyer.examples.BankProc Maven / Gradle / Ivy

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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.simprocs.*;
import umontreal.iro.lecuyer.rng.*;
import umontreal.iro.lecuyer.randvar.*;
import umontreal.iro.lecuyer.stat.*;

public class BankProc {

   ProcessSimulator sim = new ThreadProcessSimulator();
   double   minute = 1.0 / 60.0;
   int      nbServed;           // Number of customers served so far
   double   meanDelay;          // Mean time between arrivals
   SimProcess  nextCust;        // Next customer to arrive
   Resource tellers         = new Resource (sim, 0, "The tellers");
   RandomStream  streamArr  = new MRG32k3a(); // Customer's arrivals
   ErlangGen genServ        = new ErlangConvolutionGen
                                    (new MRG32k3a(), 2, 1.0/minute);
   RandomStream  streamTeller  = new MRG32k3a(); // Number of tellers
   RandomStream  streamBalk    = new MRG32k3a(); // Balking decisions
   Tally    statServed    = new Tally ("Nb. served per day");
   Tally    avWait        = new Tally ("Average wait per day (hours)");

   class OneDay extends SimProcess {
      public OneDay(ProcessSimulator sim) { super(sim); }
      public void actions() {
         int nbTellers;         // Number of tellers today.
         nbServed = 0;
         tellers.setCapacity (0);
         tellers.waitList().initStat();
         meanDelay = 2.0 * minute;
         // It is 9:45, start arrival process.
         (nextCust = new Customer(sim)).schedule
           (ExponentialGen.nextDouble (streamArr, 1.0/meanDelay));
         delay (15.0 * minute);
         // Bank opens at 10:00, generate number of tellers.
         double u = streamTeller.nextDouble();
         if (u >= 0.2) nbTellers = 3;
         else if (u < 0.05)  nbTellers = 1;
         else nbTellers = 2;
         tellers.setCapacity (nbTellers);
         delay (1.0);   // It is 11:00, double arrival rate.
         nextCust.reschedule (nextCust.getDelay() / 2.0);
         meanDelay = minute;
         delay (3.0);   // It is 14:00, halve arrival rate.
         nextCust.reschedule (nextCust.getDelay() * 2.0);
         meanDelay = 2.0 * minute;
         delay (1.0);   // It is 15:00, bank closes.
         nextCust.cancel();
      }
   }

   class Customer extends SimProcess {
      public Customer(ProcessSimulator sim) { super(sim); }
      public void actions() {
         (nextCust = new Customer(sim)).schedule
            (ExponentialGen.nextDouble (streamArr, 1.0/meanDelay));
         if (!balk()) {
            tellers.request (1);
            delay (genServ.nextDouble());
            tellers.release (1);
            nbServed++;
         }
      }

      private boolean balk() {
         int n = tellers.waitList().size();
         return n > 9 || (n > 5 && 5.0*streamBalk.nextDouble() < n - 5);
      }
   }

   public void simulOneDay() { 
      sim.init();
      new OneDay(sim).schedule (9.75);
      sim.start();
      statServed.add (nbServed);
      avWait.add (tellers.waitList().statSize().sum());
   }

   public void simulateDays (int numDays) {
      tellers.waitList().setStatCollecting (true);
      for (int i=1; i<=numDays; i++)  simulOneDay();
      System.out.println (statServed.report());
      System.out.println (avWait.report());
   }

   public static void main (String[] args) { 
       new BankProc().simulateDays (100);
   }
}