{-# LANGUAGE Arrows, FlexibleContexts #-} -- Example: In this example, the operations of a quarry are modeled. -- -- It is described in different sources [1, 2]. So, this is chapter 10 of [2] and section 5.16 of [1]. -- -- [1] A. Alan B. Pritsker, Simulation with Visual SLAM and AweSim, 2nd ed. -- [2] Труб И.И., Объектно-ориентированное моделирование на C++: Учебный курс. - СПб.: Питер, 2006 -- -- In this example, the operations of a quarry are modeled. In the quarry, -- trucks deliver ore from three shovels to a crusher. A truck always -- returns to its assigned shovel after dumping a load at the crusher. -- There are two different truck sizes in use, twenty-ton and fifty-ton. -- The size of the truck affects its loading time at the shovel, travel -- time to the crusher, dumping time at the crusher and return trip time -- from the crusher back to the appropriate shovel. For the twenty-ton -- trucks, there loading, travel, dumping and return trip times are: -- exponentially distributed with a mean 5; a constant 2.5; exponentially -- distributed with mean 2; and a constant 1.5. The corresponding times -- for the fifty-ton trucks are: exponentially distributed with mean 10; -- a constant 3; exponentially distributed with mean 4; and a constant 2. -- To each shovel is assigned two twenty-ton trucks are one fifty-ton truck. -- The shovel queues are all ranked on a first-in, first-out basis. -- The crusher queue is ranked on truck size, largest trucks first. -- It is desired to analyze this system over 480 time units to determine -- the utilization and queue lengths associated with the shovels and crusher. import Control.Monad import Control.Monad.Trans import Control.Category import Simulation.Aivika.Trans import qualified Simulation.Aivika.Trans.Queue.Infinite as IQ import Simulation.Aivika.IO type DES = IO -- | The simulation specs. specs = Specs { spcStartTime = 0.0, spcStopTime = 480.0, spcDT = 0.1, spcMethod = RungeKutta4, spcGeneratorType = SimpleGenerator } -- | The average loading time for twenty-ton truck avgLoadingTime20 = 5 -- | A constant travel time for twenty-ton truck travelTime20 = 2.5 -- | The average dumping time for twenty-ton truck avgDumpingTime20 = 2 -- | A constant return trip time for twenty-ton truck returnTripTime20 = 1.5 -- | A priority of the twenty-ton truck (less is higher) crushingPriority20 = 2 -- | The average loading time for fifty-ton truck avgLoadingTime50 = 10 -- | A constant travel time for fifty-ton truck travelTime50 = 3 -- | The average dumping time for fifty-ton truck avgDumpingTime50 = 4 -- | A constant return trip time for fifty-ton truck returnTripTime50 = 2 -- | A priority of the fifty-ton truck (less is higher) crushingPriority50 = 1 -- | It models a truck assigned to some queue. data Truck = Truck { truckQueue :: TruckQueue, -- ^ a queue to which the truck is assigned truckTonSize :: TruckTonSize, -- ^ the truck ton size truckAvgLoadingTime :: Double, -- ^ the average loading time truckTravelTime :: Double, -- ^ a constant travel time truckCrushingPriority :: Double, -- ^ a priority for crushing (less is higher) truckAvgDumpingTime :: Double, -- ^ the average dumping time truckReturnTripTime :: Double -- ^ a constant return trip time } -- | It defines the truck ton size data TruckTonSize = TwentyTonSize | FiftyTonSize -- | Specifies a queue to which the truck is assigned data TruckQueue = TruckQueue1 | TruckQueue2 | TruckQueue3 -- | Return a truck assigned to the specified queue with the given ton size. truck :: TruckQueue -> TruckTonSize -> Truck truck tq TwentyTonSize = Truck { truckQueue = tq, truckTonSize = TwentyTonSize, truckAvgLoadingTime = avgLoadingTime20, truckTravelTime = travelTime20, truckCrushingPriority = crushingPriority20, truckAvgDumpingTime = avgDumpingTime20, truckReturnTripTime = returnTripTime20 } truck tq FiftyTonSize = Truck { truckQueue = tq, truckTonSize = FiftyTonSize, truckAvgLoadingTime = avgLoadingTime50, truckTravelTime = travelTime50, truckCrushingPriority = crushingPriority50, truckAvgDumpingTime = avgDumpingTime50, truckReturnTripTime = returnTripTime50 } model :: Simulation DES (Results DES) model = do -- create a queue for the first shovel shovelQueue1 <- runEventInStartTime IQ.newFCFSQueue -- create another queue for the second shovel shovelQueue2 <- runEventInStartTime IQ.newFCFSQueue -- create a queue for the thrid shovel shovelQueue3 <- runEventInStartTime IQ.newFCFSQueue -- add initial trucks to the queue let initShovelQueue q tq = do IQ.enqueue q \$ truck tq TwentyTonSize IQ.enqueue q \$ truck tq TwentyTonSize IQ.enqueue q \$ truck tq FiftyTonSize -- initiate the three shovel queues runEventInStartTime \$ do initShovelQueue shovelQueue1 TruckQueue1 initShovelQueue shovelQueue2 TruckQueue2 initShovelQueue shovelQueue3 TruckQueue3 -- create a priority queue for the crusher crusherQueue <- runEventInStartTime IQ.newPriorityQueue -- define how the specified truck travels from the shovel to the crusher let truckTravel t = spawnProcess \$ do holdProcess (truckTravelTime t) liftEvent \$ IQ.enqueueWithStoringPriority crusherQueue (truckCrushingPriority t) t -- define how the specified truck returns to the queue let truckReturnTrip t = spawnProcess \$ do holdProcess (truckReturnTripTime t) let q = case truckQueue t of TruckQueue1 -> shovelQueue1 TruckQueue2 -> shovelQueue2 TruckQueue3 -> shovelQueue3 liftEvent \$ IQ.enqueue q t -- utilise the crusher's activity let utiliseCrusher q t = do randomExponentialProcess_ \$ truckAvgDumpingTime t return t -- utilise the shovel's activity let utiliseShovel q t = do randomExponentialProcess_ \$ truckAvgLoadingTime t return t -- create shovel activities shovelAct1 <- newActivity \$ utiliseShovel shovelQueue1 shovelAct2 <- newActivity \$ utiliseShovel shovelQueue2 shovelAct3 <- newActivity \$ utiliseShovel shovelQueue3 -- create the crusher's activity crusherAct <- newActivity \$ utiliseCrusher crusherQueue -- define how we should iterate the crusher let crusherNet act q = proc () -> do t <- arrNet (const \$ IQ.dequeue q) -< () t' <- activityNet act -< t arrNet truckReturnTrip -< t' let shovelNet act q = proc () -> do t <- arrNet (const \$ IQ.dequeue q) -< () t' <- activityNet act -< t arrNet truckTravel -< t' -- start processing the cursher's queue runProcessInStartTime \$ iterateNet (crusherNet crusherAct crusherQueue) () -- start processing the shovel queues runProcessInStartTime \$ iterateNet (shovelNet shovelAct1 shovelQueue1) () runProcessInStartTime \$ iterateNet (shovelNet shovelAct2 shovelQueue2) () runProcessInStartTime \$ iterateNet (shovelNet shovelAct3 shovelQueue3) () -- return the simulation results in start time return \$ results [resultSource "shovelQueue" "the shovel's queue" [shovelQueue1, shovelQueue2, shovelQueue3], -- resultSource "crusherQueue" "the crusher's queue" crusherQueue, -- resultSource "shovelActvty" "the shovel's activity" [shovelAct1, shovelAct2, shovelAct3], -- resultSource "crusherActvty" "the crusher's activity" crusherAct] main = printSimulationResultsInStopTime printResultSourceInEnglish (fmap resultSummary model) specs