-- It corresponds to model MachRep1 described in document
-- Introduction to Discrete-Event Simulation and the SimPy Language
-- [http://heather.cs.ucdavis.edu/~matloff/156/PLN/DESimIntro.pdf].
-- SimPy is available on [http://simpy.sourceforge.net/].
--
-- The model description is as follows.
--
-- Two machines, which sometimes break down.
-- Up time is exponentially distributed with mean 1.0, and repair time is
-- exponentially distributed with mean 0.5. There are two repairpersons,
-- so the two machines can be repaired simultaneously if they are down
-- at the same time.
--
-- Output is long-run proportion of up time. Should get value of about
-- 0.66.
import Control.Monad.Trans
import Simulation.Aivika.Trans
import Simulation.Aivika.IO
meanUpTime = 1.0
meanRepairTime = 0.5
specs = Specs { spcStartTime = 0.0,
spcStopTime = 1000.0,
spcDT = 1.0,
spcMethod = RungeKutta4,
spcGeneratorType = SimpleGenerator }
model :: Simulation IO (Results IO)
model =
do totalUpTime <- newRef 0.0
let machine =
do upTime <-
liftParameter $
randomExponential meanUpTime
holdProcess upTime
liftEvent $
modifyRef totalUpTime (+ upTime)
repairTime <-
liftParameter $
randomExponential meanRepairTime
holdProcess repairTime
machine
runProcessInStartTime machine
runProcessInStartTime machine
let upTimeProp =
do x <- readRef totalUpTime
y <- liftDynamics time
return $ x / (2 * y)
return $
results
[resultSource
"upTimeProp"
"The long-run proportion of up time (~ 0.66)"
upTimeProp]
main =
printSimulationResultsInStopTime
printResultSourceInEnglish
model specs