-- 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]