-- 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 import Control.Monad.Trans import Simulation.Aivika.Trans import Simulation.Aivika.Lattice meanUpTime = 1.0 meanRepairTime = 0.5 specs = Specs { spcStartTime = 0.0, spcStopTime = 1000.0, spcDT = 0.1, spcMethod = RungeKutta4, spcGeneratorType = SimpleGenerator } model :: Simulation LIO (Results LIO) model = do totalUpTime <- newRef 0.0 let machine = do upTime <- liftParameter $ randomExponential meanUpTime -- -- r <- liftSimulation $ newRef 10 -- holdProcess upTime liftEvent $ modifyRef totalUpTime (+ upTime) repairTime <- liftParameter $ randomExponential meanRepairTime holdProcess repairTime machine runProcessInStartTime machine runProcessInStartTime machine let upTimeProp = do x <- readRef totalUpTime t <- liftDynamics time return $ x / (2 * t) return $ results [resultSource "upTimeProp" "The long-run proportion of up time (~ 0.66)" upTimeProp] main :: IO () main = do lat <- newRandomLattice 10 runLIO lat $ printSimulationResultsInStopTime printResultSourceInEnglish model specs