-- It corresponds to model MachRep3 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.
--
-- Variation of models MachRep1, MachRep2. Two machines, but
-- sometimes break down. Up time is exponentially distributed with mean
-- 1.0, and repair time is exponentially distributed with mean 0.5. In
-- this example, there is only one repairperson, and she is not summoned
-- until both machines are down. We find the proportion of up time. It
-- should come out to about 0.45.
module Model (model) where
import Control.Monad
import Control.Monad.Trans
import Simulation.Aivika
import Simulation.Aivika.Experiment
meanUpTime = 1.0
meanRepairTime = 0.5
model :: Simulation Results
model =
do -- number of machines currently up
nUp <- newRef 2
-- total up time for all machines
totalUpTime <- newRef 0.0
repairPerson <- newResource FCFS 1
pid1 <- newProcessId
pid2 <- newProcessId
let machine :: ProcessId -> Process ()
machine pid =
do upTime <-
liftParameter $
randomExponential meanUpTime
holdProcess upTime
liftEvent $
modifyRef totalUpTime (+ upTime)
liftEvent $
modifyRef nUp (+ (-1))
nUp' <- liftEvent $ readRef nUp
if nUp' == 1
then passivateProcess
else liftEvent $
do n <- resourceCount repairPerson
when (n == 1) $
reactivateProcess pid
requestResource repairPerson
repairTime <-
liftParameter $
randomExponential meanRepairTime
holdProcess repairTime
liftEvent $
modifyRef nUp (+ 1)
releaseResource repairPerson
machine pid
runProcessInStartTimeUsingId
pid1 (machine pid2)
runProcessInStartTimeUsingId
pid2 (machine pid1)
let upTimeProp =
do x <- readRef totalUpTime
y <- liftDynamics time
return $ x / (2 * y)
return $
results
[resultSource
"upTimeProp" "The proportion of up time"
upTimeProp,
resultSource
"totalUpTime" "Total up time"
totalUpTime,
resultSource
"runIndex" "Simulation run"
simulationIndex]