diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,5 @@ + +Version 4.3 +----- + +* Updated examples. diff --git a/aivika-experiment-chart.cabal b/aivika-experiment-chart.cabal --- a/aivika-experiment-chart.cabal +++ b/aivika-experiment-chart.cabal @@ -1,5 +1,5 @@ name: aivika-experiment-chart -version: 4.2 +version: 4.3 synopsis: Simulation experiments with charting for the Aivika library description: This package complements the Aivika and Aivika Experiment packages with @@ -93,6 +93,17 @@ examples/SingleLaneTraffic/MainUsingCairo.hs examples/SingleLaneTraffic/MainUsingDiagrams.hs examples/SingleLaneTraffic/README + examples/PERT/Model.hs + examples/PERT/Experiment.hs + examples/PERT/MainUsingCairo.hs + examples/PERT/MainUsingDiagrams.hs + examples/PERT/README + examples/TruckHaulingSituation/Model.hs + examples/TruckHaulingSituation/Experiment.hs + examples/TruckHaulingSituation/MainUsingCairo.hs + examples/TruckHaulingSituation/MainUsingDiagrams.hs + examples/TruckHaulingSituation/README + CHANGELOG.md library @@ -116,7 +127,7 @@ lens >= 3.9, data-default-class < 0.1, colour >= 2.3.3, - aivika >= 4.2, + aivika >= 4.3, aivika-experiment >= 4.0.3 extensions: MultiParamTypeClasses diff --git a/examples/MachineBreakdowns/README b/examples/MachineBreakdowns/README --- a/examples/MachineBreakdowns/README +++ b/examples/MachineBreakdowns/README @@ -1,6 +1,4 @@ -CAUTION: THE MODEL IS NOT COMPLETE YET! - Example: Machine Tool with Breakdowns It is described in different sources [1, 2]. So, this is chapter 13 of [2] and section 6.12 of [1]. diff --git a/examples/PERT/Experiment.hs b/examples/PERT/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/PERT/Experiment.hs @@ -0,0 +1,65 @@ + +module Experiment (experiment, generators) where + +import Data.Monoid + +import Control.Arrow + +import Simulation.Aivika +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart + +import qualified Simulation.Aivika.Results.Transform as T + +-- | The simulation specs. +specs = Specs { spcStartTime = 0.0, + spcStopTime = 1000.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 10000, + -- experimentRunCount = 10, + experimentTitle = "Analysis of a PERT-type Network" } + +timers = resultByName "timers" + +timer2 = timers >>> resultByIndex 0 +timer3 = timers >>> resultByIndex 1 +timer4 = timers >>> resultByIndex 2 +timer5 = timers >>> resultByIndex 3 + +projCompletion = resultByName "projCompletion" + +completionTime series = + T.tr $ + T.samplingStatsMean $ + T.arrivalProcessingTime $ + T.ArrivalTimer series + +histogramView title series = + defaultFinalHistogramView { + finalHistogramTitle = title, + finalHistogramSeries = series + } + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Completion Time", + finalStatsSeries = + completionTime timers <> + completionTime projCompletion }, + outputView $ histogramView "Node 2" $ completionTime timer2, + outputView $ histogramView "Node 3" $ completionTime timer3, + outputView $ histogramView "Node 4" $ completionTime timer3, + outputView $ histogramView "Node 5" $ completionTime timer5, + outputView $ histogramView "The Project Completion" $ + completionTime projCompletion] diff --git a/examples/PERT/MainUsingCairo.hs b/examples/PERT/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/PERT/MainUsingCairo.hs @@ -0,0 +1,12 @@ + +-- To run, package aivika-experiment-cairo must be installed. + +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart.Backend.Cairo + +import Graphics.Rendering.Chart.Backend.Cairo + +import Model +import Experiment + +main = runExperiment experiment generators (WebPageRenderer $ CairoRenderer PNG) model diff --git a/examples/PERT/MainUsingDiagrams.hs b/examples/PERT/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/PERT/MainUsingDiagrams.hs @@ -0,0 +1,14 @@ + +-- To run, package aivika-experiment-diagrams must be installed. + +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart.Backend.Diagrams + +import Graphics.Rendering.Chart.Backend.Diagrams + +import qualified Data.Map as M + +import Model +import Experiment + +main = runExperiment experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model diff --git a/examples/PERT/Model.hs b/examples/PERT/Model.hs new file mode 100644 --- /dev/null +++ b/examples/PERT/Model.hs @@ -0,0 +1,137 @@ + +{-# LANGUAGE RecursiveDo #-} + +-- Example: Analysis of a PERT-type Network +-- +-- It is described in different sources [1, 2]. So, this is chapter 14 of [2] and section 7.11 of [1]. +-- +-- PERT is a technique for evaluating and reviewing a project consisting of +-- interdependent activities. A number of books have been written that describe +-- PERT modeling and analysis procedures. A PERT network activity descriptions +-- are given in a table stated below. All activity times will be assumed to be +-- triangularly distributed. For ease of description, activities have been +-- aggregated. The activities relate to power units, instrumentation, and +-- a new assembly and involve standard types of operations. +-- +-- In the following description of the project, activity numbers are given +-- in parentheses. At the beginning of the project, three parallel activities +-- can be performed that involve: the disassembly of power units and +-- instrumentation (1); the installation of a new assembly (2); and +-- the preparation for a retrofit check (3). Cleaning, inspecting, and +-- repairing the power units (4) and calibrating the instrumentation (5) +-- can be done only after the power units and instrumentation have been +-- disassembled. Thus, activities 4 and 5 must follow activity 1 in the network. +-- Following the installation of the new assembly (2) and after the instrumentation +-- have been calibrated (5), a check of interfaces (6) and a check of +-- the new assembly (7) can be made. The retrofit check (9) can be made +-- after the assembly is checked (7) and the preparation for the retrofit +-- check (3) has been completed. The assembly and test of power units (8) +-- can be performed following the cleaning and maintenance of power units (4). +-- The project is considered completed when all nine activities are completed. +-- Since activities 6, 8, and 9 require the other activities to precede them, +-- their completion signifies the end of the project. This is indicated on +-- the network by having activities 6, 8, and 9 incident to node 6, the sink +-- node for the project. The objective of this example is to illustrate +-- the procedures for using Aivika to model and simulate project planning network. +-- +-- Activity Description Mode Minimum Maximum Average +-- +-- 1 Disassemble power units and instrumentation 3 1 5 3 +-- 2 Install new assembly 6 3 9 6 +-- 3 Prepare for retrofit check 13 10 19 14 +-- 4 Clean, inspect, and repair power units 9 3 12 8 +-- 5 Calibrate instrumentation 3 1 8 4 +-- 6 Check interfaces 9 8 16 11 +-- 7 Check assembly 7 4 13 8 +-- 8 Assemble and test power units 6 3 9 6 +-- 9 Retrofit check 3 1 8 4 +-- +-- Node Depends of Activities +-- +-- 1 - +-- 2 1 +-- 3 2, 5 +-- 4 3, 7 +-- 5 4 +-- 6 6, 8, 9 +-- +-- Activity Depends on Node +-- +-- 1 1 +-- 2 1 +-- 3 1 +-- 4 2 +-- 5 2 +-- 6 3 +-- 7 3 +-- 8 5 +-- 9 4 +-- +-- [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 + +module Model (model) where + +import Control.Monad +import Control.Monad.Trans +import Control.Arrow + +import Data.Array +import Data.Maybe +import Data.Monoid + +import Simulation.Aivika + +model :: Simulation Results +model = mdo + timers' <- forM [2..5] $ \i -> newArrivalTimer + projCompletionTimer <- newArrivalTimer + let timers = array (2, 5) $ zip [2..] timers' + p1 = randomTriangularProcessor 1 3 5 + p2 = randomTriangularProcessor 3 6 9 + p3 = randomTriangularProcessor 10 13 19 + p4 = randomTriangularProcessor 3 9 12 + p5 = randomTriangularProcessor 1 3 8 + p6 = randomTriangularProcessor 8 9 16 + p7 = randomTriangularProcessor 4 7 13 + p8 = randomTriangularProcessor 3 6 9 + p9 = randomTriangularProcessor 1 3 8 + let c2 = arrivalTimerProcessor (timers ! 2) + c3 = arrivalTimerProcessor (timers ! 3) + c4 = arrivalTimerProcessor (timers ! 4) + c5 = arrivalTimerProcessor (timers ! 5) + c6 = arrivalTimerProcessor projCompletionTimer + [i1, i2, i3] <- cloneStream 3 n1 + [i4, i5] <- cloneStream 2 n2 + [i6, i7] <- cloneStream 2 n3 + let i9 = n4 + i8 = n5 + let s1 = runProcessor p1 i1 + s2 = runProcessor p2 i2 + s3 = runProcessor p3 i3 + s4 = runProcessor p4 i4 + s5 = runProcessor p5 i5 + s6 = runProcessor p6 i6 + s7 = runProcessor p7 i7 + s8 = runProcessor p8 i8 + s9 = runProcessor p9 i9 + let n1 = takeStream 1 $ randomStream $ return (0, 0) + n2 = runProcessor c2 s1 + n3 = runProcessor c3 $ firstArrivalStream 2 (s2 <> s5) + n4 = runProcessor c4 $ firstArrivalStream 2 (s3 <> s7) + n5 = runProcessor c5 s4 + n6 = runProcessor c6 $ firstArrivalStream 3 (s6 <> s8 <> s9) + runProcessInStartTime $ sinkStream n6 + return $ + results + [resultSource + "timers" "Timers" + timers, + -- + resultSource + "projCompletion" "Project Completion Timer" + projCompletionTimer] + +modelSummary :: Simulation Results +modelSummary = + fmap resultSummary model diff --git a/examples/PERT/README b/examples/PERT/README new file mode 100644 --- /dev/null +++ b/examples/PERT/README @@ -0,0 +1,69 @@ + +Example: Analysis of a PERT-Type Network. + +It is described in different sources [1, 2]. So, this is chapter 14 of [2] and section 7.11 of [1]. + +PERT is a technique for evaluating and reviewing a project consisting of +interdependent activities. A number of books have been written that describe +PERT modeling and analysis procedures. A PERT network activity descriptions +are given in a table stated below. All activity times will be assumed to be +triangularly distributed. For ease of description, activities have been +aggregated. The activities relate to power units, instrumentation, and +a new assembly and involve standard types of operations. + +In the following description of the project, activity numbers are given +in parentheses. At the beginning of the project, three parallel activities +can be performed that involve: the disassembly of power units and +instrumentation (1); the installation of a new assembly (2); and +the preparation for a retrofit check (3). Cleaning, inspecting, and +repairing the power units (4) and calibrating the instrumentation (5) +can be done only after the power units and instrumentation have been +disassembled. Thus, activities 4 and 5 must follow activity 1 in the network. +Following the installation of the new assembly (2) and after the instrumentation +have been calibrated (5), a check of interfaces (6) and a check of +the new assembly (7) can be made. The retrofit check (9) can be made +after the assembly is checked (7) and the preparation for the retrofit +check (3) has been completed. The assembly and test of power units (8) +can be performed following the cleaning and maintenance of power units (4). +The project is considered completed when all nine activities are completed. +Since activities 6, 8, and 9 require the other activities to precede them, +their completion signifies the end of the project. This is indicated on +the network by having activities 6, 8, and 9 incident to node 6, the sink +node for the project. The objective of this example is to illustrate +the procedures for using Aivika to model and simulate project planning network. + +Activity Description Mode Minimum Maximum Average + + 1 Disassemble power units and instrumentation 3 1 5 3 + 2 Install new assembly 6 3 9 6 + 3 Prepare for retrofit check 13 10 19 14 + 4 Clean, inspect, and repair power units 9 3 12 8 + 5 Calibrate instrumentation 3 1 8 4 + 6 Check interfaces 9 8 16 11 + 7 Check assembly 7 4 13 8 + 8 Assemble and test power units 6 3 9 6 + 9 Retrofit check 3 1 8 4 + +Node Depends of Activities + + 1 - + 2 1 + 3 2, 5 + 4 3, 7 + 5 4 + 6 6, 8, 9 + +Activity Depends on Node + + 1 1 + 2 1 + 3 1 + 4 2 + 5 2 + 6 3 + 7 3 + 8 5 + 9 4 + +[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 diff --git a/examples/TruckHaulingSituation/Experiment.hs b/examples/TruckHaulingSituation/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/TruckHaulingSituation/Experiment.hs @@ -0,0 +1,85 @@ + +{-# LANGUAGE FlexibleContexts #-} + +module Experiment (experiment, generators) where + +import Data.Monoid + +import Control.Arrow + +import Simulation.Aivika +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart + +import qualified Simulation.Aivika.Results.Transform as T + +-- | The simulation specs. +specs = Specs { spcStartTime = 0.0, + spcStopTime = 1000.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 1000, + -- experimentRunCount = 10, + experimentTitle = "A Truck Hauling Situation" } + +loadQueue = T.Queue $ resultByName "loadQueue" +loadQueueCount = T.tr $ T.queueCount loadQueue +loadQueueCountStats = T.tr $ T.queueCountStats loadQueue +loadWaitTime = T.tr $ T.queueWaitTime loadQueue + +truckQueue = T.Queue $ resultByName "truckQueue" +truckQueueCount = T.tr $ T.queueCount truckQueue +truckQueueCountStats = T.tr $ T.queueCountStats truckQueue +truckWaitTime = T.tr $ T.queueWaitTime truckQueue + +loaderQueue = T.Queue $ resultByName "loaderQueue" +loaderQueueCount = T.tr $ T.queueCount loaderQueue +loaderQueueCountStats = T.tr $ T.queueCountStats loaderQueue +loaderWaitTime = T.tr $ T.queueWaitTime loaderQueue + +loaderOps = T.Operation $ resultByName "loaderOps" +loaderUtilisationTime = T.tr $ T.operationUtilisationTime loaderOps +loaderUtilisationFactor = T.tr $ T.operationUtilisationFactor loaderOps + +statsView title series = + defaultFinalStatsView { + finalStatsTitle = title, + finalStatsSeries = series + } + +chartView title series = + defaultDeviationChartView { + deviationChartTitle = title, + deviationChartRightYSeries = series + } + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ statsView "Queue Length" $ + loadQueueCountStats <> + truckQueueCountStats <> + loaderQueueCountStats, + outputView $ chartView "Queue Load" $ + loadQueueCount <> loadQueueCountStats, + outputView $ chartView "Queue Trucks" $ + truckQueueCount <> truckQueueCountStats, + outputView $ chartView "Queue Loader" $ + loaderQueueCount <> loaderQueueCountStats, + outputView $ statsView "Queue Waiting Time" $ + loadWaitTime <> + truckWaitTime <> + loaderWaitTime, + outputView $ chartView "Loader Utilisation Chart" + loaderUtilisationFactor, + outputView $ statsView "Loader Utilisation Summary" $ + loaderUtilisationFactor <> + loaderUtilisationTime] diff --git a/examples/TruckHaulingSituation/MainUsingCairo.hs b/examples/TruckHaulingSituation/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/TruckHaulingSituation/MainUsingCairo.hs @@ -0,0 +1,12 @@ + +-- To run, package aivika-experiment-cairo must be installed. + +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart.Backend.Cairo + +import Graphics.Rendering.Chart.Backend.Cairo + +import Model +import Experiment + +main = runExperiment experiment generators (WebPageRenderer $ CairoRenderer PNG) model diff --git a/examples/TruckHaulingSituation/MainUsingDiagrams.hs b/examples/TruckHaulingSituation/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/TruckHaulingSituation/MainUsingDiagrams.hs @@ -0,0 +1,14 @@ + +-- To run, package aivika-experiment-diagrams must be installed. + +import Simulation.Aivika.Experiment +import Simulation.Aivika.Experiment.Chart.Backend.Diagrams + +import Graphics.Rendering.Chart.Backend.Diagrams + +import qualified Data.Map as M + +import Model +import Experiment + +main = runExperiment experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model diff --git a/examples/TruckHaulingSituation/Model.hs b/examples/TruckHaulingSituation/Model.hs new file mode 100644 --- /dev/null +++ b/examples/TruckHaulingSituation/Model.hs @@ -0,0 +1,127 @@ + +-- Example: A Truck Hauling Situation +-- +-- It is described in different sources [1, 2]. So, this is chapter 9 of [2] and section 7.16 of [1]. +-- +-- The system to be modeled in this example consists of one bulldozer, four trucks, +-- and two man-machine loaders. The bulldozer stockpiles material for the loaders. +-- Two piles of material must be stocked prior to the initiation of any load operation. +-- The time for the bulldozer to stockpile material is Erlang distributed and consists +-- of the sum of two exponential variables each with a men of 4. (This corresponds to +-- an Erlang variable with a mean of 8 and a variance of 32.) In addition to this +-- material, a loader and an unloaded truck must be available before the loading +-- operations can begin. Loading time is exponentially distributed with a mean time of +-- 14 minutes for server 1 and 12 minutes for server 2. +-- +-- After a truck is loaded, it is hauled, then dumped and must be returned before +-- the truck is available for further loading. Hauling time is normally distributed. +-- When loaded, the average hauling time is 22 minutes. When unloaded, the average +-- time is 18 minutes. In both cases, the standard deviation is 3 minutes. Dumping +-- time is uniformly distributed between 2 and 8 minutes. Following a loading +-- operation, the loaded must rest for a 5 minute period before he is available +-- to begin loading again. The system is to be analyzed for 8 hours and all operations +-- in progress at the end of 8 hours should be completed before terminating +-- the operations for a run. +-- +-- [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 + +module Model (model) where + +import Control.Monad +import Control.Monad.Trans +import Control.Arrow + +import Data.Monoid +import Data.List +import Data.Array + +import Simulation.Aivika +import qualified Simulation.Aivika.Queue.Infinite as IQ + +data Truck = Truck + +data Pile = Pile + +data Loader = Loader1 + | Loader2 + deriving (Eq, Ord, Show, Ix) + +awaitQueuesNonEmpty q1 q2 q3 = + do n1 <- liftEvent $ IQ.queueCount q1 + n2 <- liftEvent $ IQ.queueCount q2 + n3 <- liftEvent $ IQ.queueCount q3 + when (n1 == 0 || n2 == 0 || n3 == 0) $ + do let signal = IQ.queueCountChanged_ q1 <> + IQ.queueCountChanged_ q2 <> + IQ.queueCountChanged_ q3 + processAwait signal + awaitQueuesNonEmpty q1 q2 q3 + +-- | The simulation model. +model :: Simulation Results +model = do + truckQueue <- runEventInStartTime IQ.newFCFSQueue + loadQueue <- runEventInStartTime IQ.newFCFSQueue + loaderQueue <- runEventInStartTime IQ.newFCFSQueue + loaderOp1 <- runEventInStartTime $ + newRandomExponentialOperation 14 + loaderOp2 <- runEventInStartTime $ + newRandomExponentialOperation 12 + let loaderOps = array (Loader1, Loader2) + [(Loader1, loaderOp1), + (Loader2, loaderOp2)] + let start :: Process () + start = + do randomErlangProcess_ 4 2 + randomErlangProcess_ 4 2 + liftEvent $ + IQ.enqueue loadQueue Pile + t <- liftDynamics time + when (t <= 480) start + begin :: Process () + begin = + do awaitQueuesNonEmpty truckQueue loadQueue loaderQueue + truck <- IQ.dequeue truckQueue + pile <- IQ.dequeue loadQueue + loader <- IQ.dequeue loaderQueue + -- the load operation + operationProcess (loaderOps ! loader) () + -- truck hauling + liftEvent $ + do runProcess $ + do holdProcess 5 + liftEvent $ + IQ.enqueue loaderQueue loader + runProcess $ + do randomNormalProcess_ 22 3 + randomUniformProcess_ 2 8 + randomNormalProcess_ 18 3 + liftEvent $ + IQ.enqueue truckQueue truck + begin + runEventInStartTime $ + do forM_ [1..4] $ \i -> + IQ.enqueue truckQueue Truck + IQ.enqueue loaderQueue Loader1 + IQ.enqueue loaderQueue Loader2 + runProcessInStartTime begin + runProcessInStartTime begin + runProcessInStartTime start + return $ + results + [ resultSource + "loadQueue" "Queue Load" + loadQueue, + -- + resultSource + "truckQueue" "Queue Trucks" + truckQueue, + -- + resultSource + "loaderQueue" "Queue Loader" + loaderQueue, + -- + resultSource + "loaderOps" "Loader Operations" + loaderOps] diff --git a/examples/TruckHaulingSituation/README b/examples/TruckHaulingSituation/README new file mode 100644 --- /dev/null +++ b/examples/TruckHaulingSituation/README @@ -0,0 +1,27 @@ + +Example: A Truck Hauling Situation. + +It is described in different sources [1, 2]. So, this is chapter 9 of [2] and section 7.16 of [1]. + +The system to be modeled in this example consists of one bulldozer, four trucks, +and two man-machine loaders. The bulldozer stockpiles material for the loaders. +Two piles of material must be stocked prior to the initiation of any load operation. +The time for the bulldozer to stockpile material is Erlang distributed and consists +of the sum of two exponential variables each with a men of 4. (This corresponds to +an Erlang variable with a mean of 8 and a variance of 32.) In addition to this +material, a loader and an unloaded truck must be available before the loading +operations can begin. Loading time is exponentially distributed with a mean time of +14 minutes for server 1 and 12 minutes for server 2. + +After a truck is loaded, it is hauled, then dumped and must be returned before +the truck is available for further loading. Hauling time is normally distributed. +When loaded, the average hauling time is 22 minutes. When unloaded, the average +time is 18 minutes. In both cases, the standard deviation is 3 minutes. Dumping +time is uniformly distributed between 2 and 8 minutes. Following a loading +operation, the loaded must rest for a 5 minute period before he is available +to begin loading again. The system is to be analyzed for 8 hours and all operations +in progress at the end of 8 hours should be completed before terminating +the operations for a run. + +[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