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: 4.0.3 +version: 4.2 synopsis: Simulation experiments with charting for the Aivika library description: This package complements the Aivika and Aivika Experiment packages with @@ -58,6 +58,11 @@ examples/InspectionAdjustmentStations/MainUsingCairo.hs examples/InspectionAdjustmentStations/MainUsingDiagrams.hs examples/InspectionAdjustmentStations/README + examples/InventorySystem/Model.hs + examples/InventorySystem/Experiment.hs + examples/InventorySystem/MainUsingCairo.hs + examples/InventorySystem/MainUsingDiagrams.hs + examples/InventorySystem/README examples/LinearArray/Model.hs examples/LinearArray/Experiment.hs examples/LinearArray/MainUsingCairo.hs @@ -68,6 +73,26 @@ examples/MachRep3/MainUsingCairo.hs examples/MachRep3/MainUsingDiagrams.hs examples/MachRep3/README + examples/MachineBreakdowns/Model.hs + examples/MachineBreakdowns/Experiment.hs + examples/MachineBreakdowns/MainUsingCairo.hs + examples/MachineBreakdowns/MainUsingDiagrams.hs + examples/MachineBreakdowns/README + examples/QuarryOperations/Model.hs + examples/QuarryOperations/Experiment.hs + examples/QuarryOperations/MainUsingCairo.hs + examples/QuarryOperations/MainUsingDiagrams.hs + examples/QuarryOperations/README + examples/PortOperations/Model.hs + examples/PortOperations/Experiment.hs + examples/PortOperations/MainUsingCairo.hs + examples/PortOperations/MainUsingDiagrams.hs + examples/PortOperations/README + examples/SingleLaneTraffic/Model.hs + examples/SingleLaneTraffic/Experiment.hs + examples/SingleLaneTraffic/MainUsingCairo.hs + examples/SingleLaneTraffic/MainUsingDiagrams.hs + examples/SingleLaneTraffic/README library @@ -91,7 +116,7 @@ lens >= 3.9, data-default-class < 0.1, colour >= 2.3.3, - aivika >= 4.0.3, + aivika >= 4.2, aivika-experiment >= 4.0.3 extensions: MultiParamTypeClasses diff --git a/examples/BassDiffusion/Experiment.hs b/examples/BassDiffusion/Experiment.hs --- a/examples/BassDiffusion/Experiment.hs +++ b/examples/BassDiffusion/Experiment.hs @@ -20,15 +20,16 @@ experimentRunCount = 20, experimentDescription = "This is the famous Bass Diffusion model solved with help of the agent-based modelling." } +potentialAdopters = resultByName "potentialAdopters" +adopters = resultByName "adopters" + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, outputView defaultInfoView, outputView $ defaultDeviationChartView { deviationChartLeftYSeries = - resultByName "potentialAdopters" <> - resultByName "adopters" }, + potentialAdopters <> adopters }, outputView $ defaultTimeSeriesView { timeSeriesLeftYSeries = - resultByName "potentialAdopters" <> - resultByName "adopters" } ] + potentialAdopters <> adopters } ] diff --git a/examples/BouncingBall/Experiment.hs b/examples/BouncingBall/Experiment.hs --- a/examples/BouncingBall/Experiment.hs +++ b/examples/BouncingBall/Experiment.hs @@ -22,22 +22,21 @@ experimentDescription = "Simulation of a Bouncing Ball as described in " ++ "the corresponded MATLAB & Simulink example" } +t = resultByName "t" +x = resultByName "x" +v = resultByName "v" + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, outputView defaultInfoView, outputView $ defaultTableView { - tableSeries = - resultByName "t" <> - resultByName "x" <> - resultByName "v" }, + tableSeries = t <> x <> v }, outputView $ defaultTimeSeriesView { timeSeriesDescription = "The chart shows the position of the ball", timeSeriesTitle = "Position", - timeSeriesLeftYSeries = - resultByName "x" }, + timeSeriesLeftYSeries = x }, outputView $ defaultTimeSeriesView { timeSeriesDescription = "The chart shows the velocity of the ball", timeSeriesTitle = "Velocity", - timeSeriesLeftYSeries = - resultByName "v" } ] + timeSeriesLeftYSeries = v } ] diff --git a/examples/ChemicalReaction/Experiment.hs b/examples/ChemicalReaction/Experiment.hs --- a/examples/ChemicalReaction/Experiment.hs +++ b/examples/ChemicalReaction/Experiment.hs @@ -22,50 +22,35 @@ experimentDescription = "Chemical Reaction as described in " ++ "the 5-minute tutorial of Berkeley-Madonna" } +t = resultByName "t" +a = resultByName "a" +b = resultByName "b" +c = resultByName "c" + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, outputView $ defaultLastValueView { - lastValueSeries = - resultByName "t" <> - resultByName "a" <> - resultByName "b" <> - resultByName "c" }, + lastValueSeries = t <> a <> b <> c }, outputView $ defaultTableView { - tableSeries = - resultByName "t" <> - resultByName "a" <> - resultByName "b" <> - resultByName "c" }, + tableSeries = t <> a <> b <> c }, outputView $ defaultTimeSeriesView { timeSeriesTitle = "Time Series", - timeSeriesLeftYSeries = - resultByName "a" <> - resultByName "b" <> - resultByName "c" }, + timeSeriesLeftYSeries = a <> b <> c }, outputView $ defaultXYChartView { xyChartTitle = "XYChart - 1", xyChartPlotTitle = "b=b(a), c=c(a)", - xyChartXSeries = - resultByName "a", - xyChartLeftYSeries = - resultByName "b", - xyChartRightYSeries = - resultByName "c" }, + xyChartXSeries = a, + xyChartLeftYSeries = b, + xyChartRightYSeries = c }, outputView $ defaultXYChartView { xyChartTitle = "XYChart - 2", xyChartPlotTitle = "a=a(b), c=c(b)", - xyChartXSeries = - resultByName "b", - xyChartRightYSeries = - resultByName "a" <> - resultByName "c" }, + xyChartXSeries = b, + xyChartRightYSeries = a <> c }, outputView $ defaultXYChartView { xyChartTitle = "XYChart - 3", xyChartPlotTitle = "a=a(c), b=b(c)", - xyChartXSeries = - resultByName "c", - xyChartLeftYSeries = - resultByName "b", - xyChartRightYSeries = - resultByName "a" } ] + xyChartXSeries = c, + xyChartLeftYSeries = b, + xyChartRightYSeries = a } ] diff --git a/examples/DifferenceEquations/Experiment.hs b/examples/DifferenceEquations/Experiment.hs --- a/examples/DifferenceEquations/Experiment.hs +++ b/examples/DifferenceEquations/Experiment.hs @@ -23,29 +23,29 @@ "the corresponded tutorial of Berkeley-Madonna " ++ "with small modification for calculating std." } +t = resultByName "t" +x = resultByName "x" +sumX = resultByName "sumX" +sumX2 = resultByName "sumX2" +avg = resultByName "avg" +std = resultByName "std" + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, outputView defaultInfoView, outputView $ defaultTableView { tableSeries = - mconcat $ map resultByName $ - ["t", "x", "sumX", "sumX2", "avg", "std"] }, + t <> x <> sumX <> sumX2 <> avg <> std }, outputView $ defaultTimeSeriesView { timeSeriesTitle = "Time Series", - timeSeriesLeftYSeries = - resultByName "x" <> - resultByName "avg" }, + timeSeriesLeftYSeries = x <> avg }, outputView $ defaultTimingStatsView { - timingStatsSeries = - resultByName "x" }, + timingStatsSeries = x }, outputView $ defaultTimeSeriesView { timeSeriesTitle = "Sums", - timeSeriesLeftYSeries = - resultByName "sumX", - timeSeriesRightYSeries = - resultByName "sumX2" }, + timeSeriesLeftYSeries = sumX, + timeSeriesRightYSeries = sumX2 }, outputView $ defaultTimeSeriesView { timeSeriesTitle = "Standard Deviation", - timeSeriesLeftYSeries = - resultByName "std" } ] + timeSeriesLeftYSeries = std } ] diff --git a/examples/Financial/Experiment.hs b/examples/Financial/Experiment.hs --- a/examples/Financial/Experiment.hs +++ b/examples/Financial/Experiment.hs @@ -25,6 +25,12 @@ experimentDescription = "Financial Model (the Monte-Carlo simulation) as described in " ++ "Vensim 5 Modeling Guide, Chapter Financial Modeling and Risk." } +netIncome = resultByName netIncomeName +npvIncome = resultByName npvIncomeName + +netCashFlow = resultByName netCashFlowName +npvCashFlow = resultByName npvCashFlowName + monteCarloGenerators :: ChartRendering r => [WebPageGenerator r] monteCarloGenerators = [outputView defaultExperimentSpecsView, @@ -32,37 +38,25 @@ outputView $ defaultDeviationChartView { deviationChartTitle = "Chart 1", deviationChartPlotTitle = "The deviation chart for Net Income and Cash Flow", - deviationChartLeftYSeries = - resultByName netIncomeName <> - resultByName netCashFlowName }, + deviationChartLeftYSeries = netIncome <> netCashFlow }, outputView $ defaultDeviationChartView { deviationChartTitle = "Chart 2", deviationChartPlotTitle = "The deviation chart for Net Present Value of Income and Cash Flow", - deviationChartLeftYSeries = - resultByName npvIncomeName <> - resultByName npvCashFlowName }, + deviationChartLeftYSeries = npvIncome <> npvCashFlow }, outputView $ defaultFinalHistogramView { finalHistogramTitle = "Histogram 1", finalHistogramPlotTitle = "Histogram for Net Income and Cash Flow", - finalHistogramSeries = - resultByName netIncomeName <> - resultByName netCashFlowName }, + finalHistogramSeries = netIncome <> netCashFlow }, outputView $ defaultFinalHistogramView { finalHistogramTitle = "Histogram 2", finalHistogramPlotTitle = "Histogram for Net Present Value of Income and Cash Flow", - finalHistogramSeries = - resultByName npvIncomeName <> - resultByName npvCashFlowName }, + finalHistogramSeries = npvIncome <> npvCashFlow }, outputView $ defaultFinalStatsView { finalStatsTitle = "Summary 1", - finalStatsSeries = - resultByName netIncomeName <> - resultByName netCashFlowName }, + finalStatsSeries = netIncome <> netCashFlow }, outputView $ defaultFinalStatsView { finalStatsTitle = "Summary 2", - finalStatsSeries = - resultByName npvIncomeName <> - resultByName npvCashFlowName } ] + finalStatsSeries = npvIncome <> npvCashFlow } ] -- | The experiment with single simulation run. singleExperiment :: Experiment @@ -80,18 +74,11 @@ outputView $ defaultTimeSeriesView { timeSeriesTitle = "Time Series 1", timeSeriesPlotTitle = "Time series of Net Income and Cash Flow", - timeSeriesLeftYSeries = - resultByName netIncomeName <> - resultByName netCashFlowName }, + timeSeriesLeftYSeries = netIncome <> netCashFlow }, outputView $ defaultTimeSeriesView { timeSeriesTitle = "Time Series 2", timeSeriesPlotTitle = "Time series of Net Present Value for Income and Cash Flow", - timeSeriesLeftYSeries = - resultByName npvIncomeName <> - resultByName npvCashFlowName }, + timeSeriesLeftYSeries = npvIncome <> npvCashFlow }, outputView $ defaultTableView { tableTitle = "Table", - tableSeries = - mconcat $ map resultByName $ - [netIncomeName, netCashFlowName, - npvIncomeName, npvCashFlowName] } ] + tableSeries = netIncome <> netCashFlow <> npvIncome <> npvCashFlow } ] diff --git a/examples/Furnace/Experiment.hs b/examples/Furnace/Experiment.hs --- a/examples/Furnace/Experiment.hs +++ b/examples/Furnace/Experiment.hs @@ -8,6 +8,8 @@ import Simulation.Aivika.Experiment import Simulation.Aivika.Experiment.Chart +import qualified Simulation.Aivika.Results.Transform as T + import Model -- | The simulation specs. @@ -27,6 +29,19 @@ experimentRunCount = 100, experimentTitle = "The Furnace model (the Monte-Carlo simulation)" } +inputIngotCount = resultByName inputIngotCountName +loadedIngotCount = resultByName loadedIngotCountName +outputIngotCount = resultByName outputIngotCountName +pitCount = resultByName pitCountName +heatingTime = resultByName heatingTimeName +outputIngotTemp = resultByName outputIngotTempName + +furnaceQueue = T.Queue $ resultByName furnaceQueueName +furnaceQueueCount = T.tr $ T.queueCount furnaceQueue +furnaceQueueCountStats = T.tr $ T.queueCountStats furnaceQueue +furnaceQueueWaitTime = T.tr $ T.queueWaitTime furnaceQueue +furnaceQueueRate = T.tr $ T.queueRate furnaceQueue + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, @@ -35,97 +50,77 @@ deviationChartTitle = "Deviation Chart - 1", deviationChartPlotTitle = "The input, loaded and output ingot counts", deviationChartRightYSeries = - resultByName inputIngotCountName <> - resultByName loadedIngotCountName <> - resultByName outputIngotCountName }, + inputIngotCount <> loadedIngotCount <> outputIngotCount }, outputView $ defaultFinalHistogramView { finalHistogramTitle = "Final Histogram - 1", finalHistogramPlotTitle = "The distribution of input, loaded and output " ++ "ingot counts in the final time point.", finalHistogramSeries = - resultByName inputIngotCountName <> - resultByName loadedIngotCountName <> - resultByName outputIngotCountName }, + inputIngotCount <> loadedIngotCount <> outputIngotCount }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 1", finalStatsDescription = "The summary of input, loaded and output " ++ "ingot counts in the final time point.", finalStatsSeries = - resultByName inputIngotCountName <> - resultByName loadedIngotCountName <> - resultByName outputIngotCountName }, + inputIngotCount <> loadedIngotCount <> outputIngotCount }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 2", deviationChartPlotTitle = "The used pit count", - deviationChartRightYSeries = - resultByName pitCountName }, + deviationChartRightYSeries = pitCount }, outputView $ defaultFinalHistogramView { finalHistogramTitle = "Final Histogram - 2", finalHistogramPlotTitle = "The used pit count in the final time point.", - finalHistogramSeries = - resultByName pitCountName }, + finalHistogramSeries = pitCount }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 2", finalStatsDescription = "The summary of the used pit count in the final time point.", - finalStatsSeries = - resultByName pitCountName }, + finalStatsSeries = pitCount }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 3", - deviationChartPlotTitle = "The average queue size", - deviationChartRightYSeries = - resultByName furnaceQueueName >>> resultById QueueCountStatsId }, + deviationChartPlotTitle = "The queue size", + deviationChartRightYSeries = furnaceQueueCount <> furnaceQueueCountStats }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 3", finalStatsDescription = "The summary of the average queue size in the final time point.", - finalStatsSeries = - resultByName furnaceQueueName >>> resultById QueueCountStatsId }, + finalStatsSeries = furnaceQueueCountStats }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 4", deviationChartPlotTitle = "The mean wait time", - deviationChartRightYSeries = - resultByName furnaceQueueName >>> resultById QueueWaitTimeId }, + deviationChartRightYSeries = furnaceQueueWaitTime }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 4", finalStatsDescription = "The summary of the mean wait time in " ++ "the final time point.", - finalStatsSeries = - resultByName furnaceQueueName >>> resultById QueueWaitTimeId }, + finalStatsSeries = furnaceQueueWaitTime }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 5", deviationChartPlotTitle = "The queue rate", - deviationChartRightYSeries = - resultByName furnaceQueueName >>> resultById QueueRateId }, + deviationChartRightYSeries = furnaceQueueRate }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 5", finalStatsDescription = "The summary of the queue rate in " ++ "the final time point.", - finalStatsSeries = - resultByName furnaceQueueName >>> resultById QueueRateId }, + finalStatsSeries = furnaceQueueRate }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 6", deviationChartPlotTitle = "The mean heating time", - deviationChartRightYSeries = - resultByName heatingTimeName }, + deviationChartRightYSeries = heatingTime }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 6", finalStatsDescription = "The summary of the mean heating time in " ++ "the final time point.", - finalStatsSeries = - resultByName heatingTimeName }, + finalStatsSeries = heatingTime }, outputView $ defaultDeviationChartView { deviationChartTitle = "Deviation Chart - 7", deviationChartPlotTitle = "The output ingot temperature", - deviationChartRightYSeries = - resultByName outputIngotTempName }, + deviationChartRightYSeries = outputIngotTemp }, outputView $ defaultFinalHistogramView { finalHistogramTitle = "Final Histogram - 7", finalHistogramPlotTitle = "The output ingot temperature in " ++ "the final time point.", - finalHistogramSeries = - resultByName outputIngotTempName }, + finalHistogramSeries = outputIngotTemp }, outputView $ defaultFinalStatsView { finalStatsTitle = "Final Statistics - 7", finalStatsDescription = "The summary of the output ingot temperature in " ++ "the final time point.", - finalStatsSeries = - resultByName outputIngotTempName } ] + finalStatsSeries = outputIngotTemp } ] diff --git a/examples/InspectionAdjustmentStations/Experiment.hs b/examples/InspectionAdjustmentStations/Experiment.hs --- a/examples/InspectionAdjustmentStations/Experiment.hs +++ b/examples/InspectionAdjustmentStations/Experiment.hs @@ -9,6 +9,8 @@ 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 = 480.0, @@ -25,37 +27,32 @@ -- experimentRunCount = 10, experimentTitle = "Inspection and Adjustment Stations on a Production Line (the Monte-Carlo simulation)" } +inputArrivalTimer = T.ArrivalTimer $ resultByName "inputArrivalTimer" +outputArrivalTimer = T.ArrivalTimer $ resultByName "outputArrivalTimer" + +inspectionStations = T.Server $ resultByName "inspectionStations" +adjustmentStations = T.Server $ resultByName "adjustmentStations" + +inspectionQueue = T.Queue $ resultByName "inspectionQueue" +adjustmentQueue = T.Queue $ resultByName "adjustmentQueue" + resultProcessingTime :: ResultTransform resultProcessingTime = - (resultByName "inputArrivalTimer" >>> - resultById ArrivalProcessingTimeId) - <> - (resultByName "outputArrivalTimer" >>> - resultById ArrivalProcessingTimeId) + (T.tr $ T.arrivalProcessingTime inputArrivalTimer) <> + (T.tr $ T.arrivalProcessingTime outputArrivalTimer) resultProcessingFactor :: ResultTransform resultProcessingFactor = - (resultByName "inspectionStations" >>> - resultById ServerProcessingFactorId) - <> - (resultByName "adjustmentStations" >>> - resultById ServerProcessingFactorId) + (T.tr $ T.serverProcessingFactor inspectionStations) <> + (T.tr $ T.serverProcessingFactor adjustmentStations) -resultQueueSize :: ResultTransform -resultQueueSize = - (resultByName "inspectionQueue" >>> - resultById QueueCountStatsId) - <> - (resultByName "adjustmentQueue" >>> - resultById QueueCountStatsId) +inspectionQueueCount = T.tr $ T.queueCount inspectionQueue +inspectionQueueCountStats = T.tr $ T.queueCountStats inspectionQueue +inspectionWaitTime = T.tr $ T.queueWaitTime inspectionQueue -resultWaitTime :: ResultTransform -resultWaitTime = - (resultByName "inspectionQueue" >>> - resultById QueueWaitTimeId) - <> - (resultByName "adjustmentQueue" >>> - resultById QueueWaitTimeId) +adjustmentQueueCount = T.tr $ T.queueCount adjustmentQueue +adjustmentQueueCountStats = T.tr $ T.queueCountStats adjustmentQueue +adjustmentWaitTime = T.tr $ T.queueWaitTime adjustmentQueue generators :: ChartRendering r => [WebPageGenerator r] generators = @@ -76,16 +73,32 @@ finalStatsTitle = "The processing factor (statistics)", finalStatsSeries = resultProcessingFactor }, outputView $ defaultDeviationChartView { - deviationChartTitle = "The queue size (chart)", + deviationChartTitle = "The inspection queue size (chart)", deviationChartWidth = 1000, - deviationChartRightYSeries = resultQueueSize }, + deviationChartRightYSeries = + inspectionQueueCount <> inspectionQueueCountStats }, outputView $ defaultFinalStatsView { - finalStatsTitle = "The queue size (statistics)", - finalStatsSeries = resultQueueSize }, + finalStatsTitle = "The inspection queue size (statistics)", + finalStatsSeries = inspectionQueueCountStats }, outputView $ defaultDeviationChartView { - deviationChartTitle = "The queue wait time (chart)", + deviationChartTitle = "The inspection queue wait time (chart)", deviationChartWidth = 1000, - deviationChartRightYSeries = resultWaitTime }, + deviationChartRightYSeries = inspectionWaitTime }, outputView $ defaultFinalStatsView { - finalStatsTitle = "The queue wait time (statistics)", - finalStatsSeries = resultWaitTime } ] + finalStatsTitle = "The inspection queue wait time (statistics)", + finalStatsSeries = inspectionWaitTime }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The adjustment queue size (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = + adjustmentQueueCount <> adjustmentQueueCountStats }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The adjustment queue size (statistics)", + finalStatsSeries = adjustmentQueueCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The adjustment queue wait time (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = adjustmentWaitTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The adjustment queue wait time (statistics)", + finalStatsSeries = adjustmentWaitTime } ] diff --git a/examples/InventorySystem/Experiment.hs b/examples/InventorySystem/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/InventorySystem/Experiment.hs @@ -0,0 +1,76 @@ + +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 = 312.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 1000, + -- experimentRunCount = 10, + experimentTitle = "Inventory System with Lost Sales and Backorders" } + +radio = T.Resource $ resultByName "radio" +radioCount = T.tr $ T.resourceCount radio +radioCountStats = T.tr $ T.resourceCountStats radio + +invPos = T.TimingCounter $ resultByName "invPos" +invPosValue = T.tr $ T.timingCounterValue invPos +invPosStats = T.tr $ T.timingCounterStats invPos + +tbLostSales = resultByName "tbLostSales" +tbLostSalesCount = + T.tr $ + T.samplingStatsCount $ + T.SamplingStats tbLostSales + +safetyStock :: ResultTransform +safetyStock = resultByName "safetyStock" + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ defaultFinalStatsView { + finalStatsTitle = "Inventory Position and Time Between Lost Sales", + finalStatsSeries = invPosStats <> tbLostSales }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "Radios and Inventory Position", + -- deviationChartWidth = 1000, + deviationChartRightYSeries = + radioCount <> invPosValue }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "Radios", + -- deviationChartWidth = 1000, + deviationChartRightYSeries = + radioCount <> radioCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "Inventory Position", + -- deviationChartWidth = 1000, + deviationChartRightYSeries = + invPosValue <> invPosStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "Safety Stock", + -- deviationChartWidth = 1000, + deviationChartRightYSeries = + safetyStock }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "Safety Stock", + finalStatsSeries = safetyStock } ] diff --git a/examples/InventorySystem/MainUsingCairo.hs b/examples/InventorySystem/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/InventorySystem/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/InventorySystem/MainUsingDiagrams.hs b/examples/InventorySystem/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/InventorySystem/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/InventorySystem/Model.hs b/examples/InventorySystem/Model.hs new file mode 100644 --- /dev/null +++ b/examples/InventorySystem/Model.hs @@ -0,0 +1,162 @@ + +-- Example: Inventory System with Lost Sales and Backorders +-- +-- It is described in different sources [1, 2]. So, this is chapter 11 of [2] and section 6.7 of [1]. +-- +-- A large discount house is planning to install a system to control the inventory of +-- a particular radio. The time between demands for a radio is exponentially distributed +-- with a mean time of 0.2 weeks. In the case where customers demand the radio when it +-- is not in stock, 80 percent will go to another nearby discount house to find it, thereby +-- representing lost sales, while the other 20 percent will backorder the radio and wait +-- for the next shipment arrival. The store employs a periodic review-reorder point +-- inventory system where the inventory status is reviewed every four weeks to decide if +-- an order should be placed. The company policy is to order up to the stock control level +-- of 72 radios whenever the inventory position, consisting of the radios in stock plus +-- the radios on order minus the radios on backorder, is found to be less than or equal to +-- the reorder point of 18 radios. The procurement lead time (the time from the placement +-- of an order to its receipt) is constant and requires three weeks. +-- +-- The objective of this example is to simulate the inventory system for a period of six +-- years (312 weeks) to obtain statistics on the following quantities: +-- +-- 1) number of radios in stock; +-- 2) inventory position; +-- 3) safety stock (radios in stock at order receipt times); and +-- 4) time between lost sales. +-- +-- The initial conditions for the simulation are an inventory position of 72 and no +-- initial backorders. In order to reduce the bias in the statistics due to the initial +-- starting conditions, all the statistics are to be cleared at the end of the first year +-- of the six year simulation period. +-- +-- [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 Simulation.Aivika +import qualified Simulation.Aivika.Resource as R + +-- | The time between demands for a radio. +avgRadioDemand = 0.2 + +-- | The percent of customers who will backorder the radio. +backorderPercent = 0.2 + +-- | The stock control level to be ordered up. +stockControlLevel = 72 + +-- | The inventory position for reordering radio. +reorderPositionThreshold = 18 + +-- | The initial radios in stock. +radio0 = 72 :: Int + +-- | The time from the placement of an order to its receipt +leadTime = 3 + +-- | How often to order the radios? +reviewPeriod = 4 + +-- | Clear the statistics at the end of the first year +clearingTime = 52 + +model :: Simulation Results +model = do + -- the start time + t0 <- liftParameter starttime + -- the inventory position + invPos <- newRef $ returnTimingCounter t0 radio0 + -- the radios in stock + radio <- runEventInStartTime $ R.newFCFSResource radio0 + -- the time between lost sales + tbLostSales <- newRef emptySamplingStats + -- the last arrive time for the lost sale + lostSaleArrive <- newRef Nothing + -- a customer order + let customerOrder :: Event () + customerOrder = do + do t <- liftDynamics time + modifyRef invPos $ + decTimingCounter t 1 + runProcess $ + R.requestResource radio + -- a customer has been lost + let customerLost :: Event () + customerLost = do + t0 <- readRef lostSaleArrive + t <- liftDynamics time + case t0 of + Nothing -> return () + Just t0 -> + modifyRef tbLostSales $ + addSamplingStats (t - t0) + writeRef lostSaleArrive (Just t) + -- a customer arrival process + let customerArrival :: Process () + customerArrival = do + randomExponentialProcess_ avgRadioDemand + liftEvent $ do + r <- R.resourceCount radio + if r > 0 + then customerOrder + else do b <- liftParameter $ + randomTrue backorderPercent + if b + then customerOrder + else customerLost + customerArrival + -- start the customer arrival process + runProcessInStartTime customerArrival + -- the safety stock + safetyStock <- newRef emptySamplingStats + -- an inventory review process + let invReview :: Process () + invReview = do + x <- liftEvent $ readRef invPos + let n = timingCounterValue x + when (n <= reorderPositionThreshold) $ + do let orderQty = stockControlLevel - n + liftEvent $ + do t <- liftDynamics time + modifyRef invPos $ + setTimingCounter t stockControlLevel + holdProcess leadTime + liftEvent $ + do r <- R.resourceCount radio + modifyRef safetyStock $ + addSamplingStats r + R.incResourceCount radio orderQty + -- start the inventory review process + runEventInStartTime $ + enqueueEventWithTimes [t0, t0 + reviewPeriod ..] $ + runProcess invReview + -- clear the statistics at the end of the first year + runEventInStartTime $ + enqueueEvent clearingTime $ + do t <- liftDynamics time + modifyRef invPos $ \x -> + returnTimingCounter t (timingCounterValue x) + writeRef tbLostSales emptySamplingStats + writeRef safetyStock emptySamplingStats + -- return the simulation results + return $ + results + [resultSource + "radio" "the number of radios in stock" + radio, + -- + resultSource + "invPos" "the inventory position" + invPos, + -- + resultSource + "tbLostSales" "the time between lost sales" + tbLostSales, + -- + resultSource + "safetyStock" "the safety stock" + safetyStock] diff --git a/examples/InventorySystem/README b/examples/InventorySystem/README new file mode 100644 --- /dev/null +++ b/examples/InventorySystem/README @@ -0,0 +1,33 @@ + +Example: Inventory System with Lost Sales and Backorders + +It is described in different sources [1, 2]. So, this is chapter 11 of [2] and section 6.7 of [1]. + +A large discount house is planning to install a system to control the inventory of +a particular radio. The time between demands for a radio is exponentially distributed +with a mean time of 0.2 weeks. In the case where customers demand the radio when it +is not in stock, 80 percent will go to another nearby discount house to find it, thereby +representing lost sales, while the other 20 percent will backorder the radio and wait +for the next shipment arrival. The store employs a periodic review-reorder point +inventory system where the inventory status is reviewed every four weeks to decide if +an order should be placed. The company policy is to order up to the stock control level +of 72 radios whenever the inventory position, consisting of the radios in stock plus +the radios on order minus the radios on backorder, is found to be less than or equal to +the reorder point of 18 radios. The procurement lead time (the time from the placement +of an order to its receipt) is constant and requires three weeks. + +The objective of this example is to simulate the inventory system for a period of six +years (312 weeks) to obtain statistics on the following quantities: + + 1) number of radios in stock; + 2) inventory position; + 3) safety stock (radios in stock at order receipt times); and + 4) time between lost sales. + +The initial conditions for the simulation are an inventory position of 72 and no +initial backorders. In order to reduce the bias in the statistics due to the initial +starting conditions, all the statistics are to be cleared at the end of the first year +of the six year simulation period. + +[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/LinearArray/Experiment.hs b/examples/LinearArray/Experiment.hs --- a/examples/LinearArray/Experiment.hs +++ b/examples/LinearArray/Experiment.hs @@ -22,51 +22,41 @@ experimentDescription = "Model Linear Array as described in " ++ "the examples included in Berkeley-Madonna." } +t = resultByName "t" +m = resultByName "m" +c = resultByName "c" + generators :: ChartRendering r => [WebPageGenerator r] generators = [outputView defaultExperimentSpecsView, outputView $ defaultTableView { - tableSeries = - resultByName "t" <> - resultByName "m" <> - resultByName "c" }, + tableSeries = t <> m <> c }, outputView $ defaultTimeSeriesView { - timeSeriesLeftYSeries = - resultByName "m", + timeSeriesLeftYSeries = m, timeSeriesWidth = 800, timeSeriesHeight = 800 }, outputView $ defaultTimeSeriesView { - timeSeriesRightYSeries = - resultByName "c", + timeSeriesRightYSeries = c, timeSeriesWidth = 800, timeSeriesHeight = 800 }, outputView $ defaultTimeSeriesView { - timeSeriesLeftYSeries = - resultByName "m", - timeSeriesRightYSeries = - resultByName "c", + timeSeriesLeftYSeries = m, + timeSeriesRightYSeries = c, timeSeriesWidth = 800, timeSeriesHeight = 800 }, outputView $ defaultXYChartView { - xyChartXSeries = - resultByName "t", - xyChartLeftYSeries = - resultByName "m", + xyChartXSeries = t, + xyChartLeftYSeries = m, xyChartWidth = 800, xyChartHeight = 800 }, outputView $ defaultXYChartView { - xyChartXSeries = - resultByName "t", - xyChartRightYSeries = - resultByName "c", + xyChartXSeries = t, + xyChartRightYSeries = c, xyChartWidth = 800, xyChartHeight = 800 }, outputView $ defaultXYChartView { - xyChartXSeries = - resultByName "t", - xyChartLeftYSeries = - resultByName "m", - xyChartRightYSeries = - resultByName "c", + xyChartXSeries = t, + xyChartLeftYSeries = m, + xyChartRightYSeries = c, xyChartWidth = 800, xyChartHeight = 800 } ] diff --git a/examples/MachineBreakdowns/Experiment.hs b/examples/MachineBreakdowns/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/MachineBreakdowns/Experiment.hs @@ -0,0 +1,97 @@ + +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 = 500.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 1000, + -- experimentRunCount = 10, + experimentTitle = "Machine Tool with Breakdowns" } + +jobsCompleted = T.ArrivalTimer $ resultByName "jobsCompleted" +jobsInterrupted = resultByName "jobsInterrupted" +inputQueue = T.Queue $ resultByName "inputQueue" +machineProcessing = T.Server $ resultByName "machineProcessing" + +jobsCompletedCount = + T.tr $ T.samplingStatsCount $ + T.arrivalProcessingTime jobsCompleted + +processingTime :: ResultTransform +processingTime = + T.tr $ T.arrivalProcessingTime jobsCompleted + +waitTime :: ResultTransform +waitTime = + T.tr $ T.queueWaitTime inputQueue + +queueCount :: ResultTransform +queueCount = + T.tr $ T.queueCount inputQueue + +queueCountStats :: ResultTransform +queueCountStats = + T.tr $ T.queueCountStats inputQueue + +processingFactor :: ResultTransform +processingFactor = + T.tr $ T.serverProcessingFactor machineProcessing + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ defaultFinalStatsView { + finalStatsTitle = "Machine Tool With Breakdowns", + finalStatsSeries = jobsCompletedCount <> jobsInterrupted }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Wait Time (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = waitTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Wait Time (statistics)", + finalStatsSeries = waitTime }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Queue Size (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = queueCount <> queueCountStats }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Queue Size (statistics)", + finalStatsSeries = queueCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Processing Time (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = processingTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Processing Time (statistics)", + finalStatsSeries = processingTime }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Machine Load (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = processingFactor }, + outputView $ defaultFinalHistogramView { + finalHistogramTitle = "The Machine Load (histogram)", + finalHistogramWidth = 1000, + finalHistogramSeries = processingFactor }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Machine Load (statistics)", + finalStatsSeries = processingFactor } ] diff --git a/examples/MachineBreakdowns/MainUsingCairo.hs b/examples/MachineBreakdowns/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/MachineBreakdowns/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 = runExperimentParallel experiment generators (WebPageRenderer $ CairoRenderer PNG) model diff --git a/examples/MachineBreakdowns/MainUsingDiagrams.hs b/examples/MachineBreakdowns/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/MachineBreakdowns/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 = runExperimentParallel experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model diff --git a/examples/MachineBreakdowns/Model.hs b/examples/MachineBreakdowns/Model.hs new file mode 100644 --- /dev/null +++ b/examples/MachineBreakdowns/Model.hs @@ -0,0 +1,146 @@ + +-- 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]. +-- +-- Jobs arrive to a machine tool on the average of one per hour. The distribution of +-- these interarrival times is exponential. During normal operation, the jobs are +-- processed on a first-in, first-out basis. The time to process a job in hours is +-- normally distributed with a mean of 0.5 and a standard deviation of 0.1. In addition +-- to the processing time, there is a set up time that is uniformly distributed between +-- 0.2 and 0.5 of an hour. Jobs that have been processed by the machine tool are routed +-- to a different section of the shop and are considered to have left the machine tool +-- area. +-- +-- The machine tool experiences breakdowns during which time it can no longer process +-- jobs. The time between breakdowns is normally distributed with a mean of 20 hours +-- and a standard deviation of 2 hours. When a breakdown occurs, the job being processed +-- is removed from the machine tool and is placed at the head of the queue of jobs +-- waiting to be processed. Jobs preempted restart from the point at which they were +-- interrupted. +-- +-- When the machine tool breaks down, a repair process is initiated which is +-- accomplished in three phases. Each phase is exponentially distributed with a mean of +-- 3/4 of an hour. Since the repair time is the sum of independent and identically +-- distributed exponential random variables, the repair time is Erlang distributed. +-- The machine tool is to be analyzed for 500 hours to obtain information on +-- the utilization of the machine tool and the time required to process a job. +-- Statistics are to be collected for thousand simulation runs. +-- +-- [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.Category + +import Data.Monoid +import Data.List + +import Simulation.Aivika +import qualified Simulation.Aivika.Queue.Infinite as IQ +import qualified Simulation.Aivika.Resource.Preemption as PR + +-- | How often do jobs arrive to a machine tool (exponential)? +jobArrivingMu = 1 + +-- | A mean of time to process a job (normal). +jobProcessingMu = 0.5 + +-- | The standard deviation of time to process a job (normal). +jobProcessingSigma = 0.1 + +-- | The minimum set-up time (uniform). +minSetUpTime = 0.2 + +-- | The maximum set-up time (uniform). +maxSetUpTime = 0.5 + +-- | A mean of time between breakdowns (normal). +breakdownMu = 20 + +-- | The standard deviation of time between breakdowns (normal). +breakdownSigma = 2 + +-- | A mean of each of the three repair phases (Erlang). +repairMu = 3/4 + +-- | A priority of the job (less is higher) +jobPriority = 1 + +-- | A priority of the breakdown (less is higher) +breakdownPriority = 0 + +-- | The simulation model. +model :: Simulation Results +model = do + -- create an input queue + inputQueue <- runEventInStartTime IQ.newFCFSQueue + -- a counter of jobs completed + jobsCompleted <- newArrivalTimer + -- a counter of interrupted jobs + jobsInterrupted <- newRef (0 :: Int) + -- create an input stream + let inputStream = + randomExponentialStream jobArrivingMu + -- create a preemptible resource + tool <- runEventInStartTime $ PR.newResource 1 + -- the machine setting up + machineSettingUp <- + newPreemptibleRandomUniformServer True minSetUpTime maxSetUpTime + -- the machine processing + machineProcessing <- + newPreemptibleRandomNormalServer True jobProcessingMu jobProcessingSigma + -- the machine breakdown + let machineBreakdown = + do randomNormalProcess_ breakdownMu breakdownSigma + PR.usingResourceWithPriority tool breakdownPriority $ + randomErlangProcess_ repairMu 3 + machineBreakdown + -- start the process of breakdowns + runProcessInStartTime machineBreakdown + -- update a counter of job interruptions + runEventInStartTime $ + handleSignal_ (serverTaskPreemptionBeginning machineProcessing) $ \a -> + modifyRef jobsInterrupted (+ 1) + -- define the queue network + let network = + queueProcessor + (\a -> liftEvent $ IQ.enqueue inputQueue a) + (IQ.dequeue inputQueue) >>> + (withinProcessor $ PR.requestResourceWithPriority tool jobPriority) >>> + serverProcessor machineSettingUp >>> + serverProcessor machineProcessing >>> + (withinProcessor $ PR.releaseResource tool) >>> + arrivalTimerProcessor jobsCompleted + -- start the machine tool + runProcessInStartTime $ + sinkStream $ runProcessor network inputStream + -- return the simulation results in start time + return $ + results + [resultSource + "inputQueue" "the queue of jobs" + inputQueue, + -- + resultSource + "machineSettingUp" "the machine setting up" + machineSettingUp, + -- + resultSource + "machineProcessing" "the machine processing" + machineProcessing, + -- + resultSource + "jobsInterrupted" "a counter of the interrupted jobs" + jobsInterrupted, + -- + resultSource + "jobsCompleted" "a counter of the completed jobs" + jobsCompleted, + -- + resultSource + "tool" "the machine tool" + tool] diff --git a/examples/MachineBreakdowns/README b/examples/MachineBreakdowns/README new file mode 100644 --- /dev/null +++ b/examples/MachineBreakdowns/README @@ -0,0 +1,33 @@ + +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]. + +Jobs arrive to a machine tool on the average of one per hour. The distribution of +these interarrival times is exponential. During normal operation, the jobs are +processed on a first-in, first-out basis. The time to process a job in hours is +normally distributed with a mean of 0.5 and a standard deviation of 0.1. In addition +to the processing time, there is a set up time that is uniformly distributed between +0.2 and 0.5 of an hour. Jobs that have been processed by the machine tool are routed +to a different section of the shop and are considered to have left the machine tool +area. + +The machine tool experiences breakdowns during which time it can no longer process +jobs. The time between breakdowns is normally distributed with a mean of 20 hours +and a standard deviation of 2 hours. When a breakdown occurs, the job being processed +is removed from the machine tool and is placed at the head of the queue of jobs +waiting to be processed. Jobs preempted restart from the point at which they were +interrupted. + +When the machine tool breaks down, a repair process is initiated which is +accomplished in three phases. Each phase is exponentially distributed with a mean of +3/4 of an hour. Since the repair time is the sum of independent and identically +distributed exponential random variables, the repair time is Erlang distributed. +The machine tool is to be analyzed for 500 hours to obtain information on +the utilization of the machine tool and the time required to process a job. +Statistics are to be collected for thousand simulation runs. + +[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/PortOperations/Experiment.hs b/examples/PortOperations/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/PortOperations/Experiment.hs @@ -0,0 +1,70 @@ + +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 = 8760.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 500, + -- experimentRunCount = 10, + experimentTitle = "Port Operations" } + +portTime = resultByName "portTime" + +berth = T.Resource $ resultByName "berth" +berthCountStats = T.tr $ T.resourceCountStats berth +berthUtilisationCount = T.tr $ T.resourceUtilisationCountStats berth +berthQueueCount = T.tr $ T.resourceQueueCount berth +berthQueueCountStats = T.tr $ T.resourceQueueCountStats berth +berthWaitTime = T.tr $ T.resourceWaitTime berth + +tug = T.Resource $ resultByName "tug" +tugCountStats = T.tr $ T.resourceCountStats tug +tugUtilisationCount = T.tr $ T.resourceUtilisationCountStats tug +tugQueueCount = T.tr $ T.resourceQueueCount tug +tugQueueCountStats = T.tr $ T.resourceQueueCountStats tug +tugWaitTime = T.tr $ T.resourceWaitTime tug + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Port Time Summary", + finalStatsSeries = portTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Queue Length", + finalStatsSeries = berthQueueCountStats <> tugQueueCountStats }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Wait Time", + finalStatsSeries = berthWaitTime <> tugWaitTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Utilisation Summary", + finalStatsSeries = berthUtilisationCount <> tugUtilisationCount }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Availability Summary", + finalStatsSeries = berthCountStats <> tugCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Berth Resource Queue Length", + deviationChartRightYSeries = berthQueueCount <> berthQueueCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Tug Resource Queue Length", + deviationChartRightYSeries = tugQueueCount <> tugQueueCountStats }] diff --git a/examples/PortOperations/MainUsingCairo.hs b/examples/PortOperations/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/PortOperations/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/PortOperations/MainUsingDiagrams.hs b/examples/PortOperations/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/PortOperations/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/PortOperations/Model.hs b/examples/PortOperations/Model.hs new file mode 100644 --- /dev/null +++ b/examples/PortOperations/Model.hs @@ -0,0 +1,157 @@ + +{-# LANGUAGE RecursiveDo #-} + +-- Example: Port Operations +-- +-- It is described in different sources [1, 2]. So, this is chapter 12 of [2] and section 6.13 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 +-- +-- A port in Africa is used to load tankers with crude oil for overwater shipment. +-- The port has facilities for loading as many as three tankers simultaneously. +-- The tankers, which arrive at the port every 11 +/- 7 hours, are of three different +-- types. The relative frequency of the various types, and their loading time +-- requirements, are as follows: +-- +-- Type Relative Frequency Loading Time, Hours +-- 1 0.25 18 +/- 2 +-- 2 0.55 24 +/- 3 +-- 3 0.20 36 +/- 4 +-- +-- There is one tug at the port. Tankers of all types require the services of this tug +-- to move into a berth, and later to move out of a berth. When the tug is available, +-- any berthing or de-berthing activity takes about one hour. Top priority is given to +-- the berthing activity. +-- +-- A shipper is considering bidding on a contract to transport oil from the port to +-- the United Kingdom. He has determined that 5 tankers of a particular type would +-- have to be committed to this task to meet contract specifications. These tankers +-- would require 21 +/- 3 hours to load oil at the port. After loading and de-berthing, +-- they would travel to the United Kingdom, offload the oil, and return to the port for +-- reloading. Their round-trip travel time, including offloading, is estimated to be +-- 240 +/- hours. +-- +-- A complicated factor is that the port experiences storms. The time between +-- the onset of storms is exponentially distributed with a mean of 48 hours and a +-- storm lasts 4 +/- 2 hours. No tug can start an operation until a storm is over. +-- +-- Before the port authorities can commit themselves to accommodating the +-- proposed 5 tankers, the effect of the additional port traffic on the in-port residence +-- time of the current port users must be determined. It is desired to simulate the +-- operation of the port for a one-year period (= 8640 hours) under the proposed new +-- commitment to measure in-port residence time of the proposed additional tankers, +-- as well as the three types of tankers which already use the port. All durations +-- given as ranges are uniformly distributed. + +module Model (model) where + +import Control.Monad +import Control.Monad.Trans + +import Data.Array + +import Simulation.Aivika +import qualified Simulation.Aivika.Resource as R + +data Tunker = + Tunker { tunkerLoadingTime :: Double, + tunkerType :: Int } + +model :: Simulation Results +model = mdo + portTime' <- forM [1..4] $ \i -> + newRef emptySamplingStats + let portTime = + array (1, 4) $ zip [1..] portTime' + berth <- + runEventInStartTime $ + R.newFCFSResource 3 + tug <- + runEventInStartTime $ + R.newFCFSResource 1 + let tunkers13 = randomUniformStream 4 18 + tunkers4 = takeStream 5 $ + randomUniformStream 48 48 + runProcessInStartTime $ + flip consumeStream tunkers13 $ \x -> + do p <- liftParameter $ + randomUniform 0 1 + let tp | p <= 0.25 = 1 + | p <= 0.25 + 0.55 = 2 + | otherwise = 3 + case tp of + 1 -> liftEvent arv1 + 2 -> liftEvent arv2 + 3 -> liftEvent arv3 + runProcessInStartTime $ + flip consumeStream tunkers4 $ \x -> + liftEvent arv4 + let arv1 :: Event () + arv1 = do + loadingTime <- liftParameter $ + randomUniform 16 20 + let t = Tunker loadingTime 1 + runProcess (port t) + arv2 :: Event () + arv2 = do + loadingTime <- liftParameter $ + randomUniform 21 27 + let t = Tunker loadingTime 2 + runProcess (port t) + arv3 :: Event () + arv3 = do + loadingTime <- liftParameter $ + randomUniform 32 40 + let t = Tunker loadingTime 3 + runProcess (port t) + arv4 :: Event () + arv4 = do + loadingTime <- liftParameter $ + randomUniform 18 24 + let t = Tunker loadingTime 4 + runProcess (port t) + let port :: Tunker -> Process () + port t = do + t0 <- liftDynamics time + R.requestResource berth + R.requestResource tug + holdProcess 1 + R.releaseResource tug + holdProcess (tunkerLoadingTime t) + R.requestResource tug + holdProcess 1 + R.releaseResource tug + R.releaseResource berth + t1 <- liftDynamics time + let tp = tunkerType t + liftEvent $ + modifyRef (portTime ! tp) $ + addSamplingStats (t1 - t0) + when (tp == 4) $ + liftEvent $ + runProcess $ + do randomUniformProcess_ 216 264 + liftEvent arv4 + storm :: Process () + storm = do + randomExponentialProcess_ 48 + R.decResourceCount tug 1 + randomUniformProcess_ 2 6 + liftEvent $ + R.incResourceCount tug 1 + storm + runProcessInStartTime storm + return $ + results + [resultSource + "portTime" "Port Time" + portTime, + -- + resultSource + "berth" "Berth" + berth, + -- + resultSource + "tug" "Tug" + tug ] diff --git a/examples/PortOperations/README b/examples/PortOperations/README new file mode 100644 --- /dev/null +++ b/examples/PortOperations/README @@ -0,0 +1,43 @@ + +Example: Port Operations + +It is described in different sources [1, 2]. So, this is chapter 12 of [2] and section 6.13 of [1]. + +A port in Africa is used to load tankers with crude oil for overwater shipment. +The port has facilities for loading as many as three tankers simultaneously. +The tankers, which arrive at the port every 11 +/- 7 hours, are of three different +types. The relative frequency of the various types, and their loading time +requirements, are as follows: + +Type Relative Frequency Loading Time, Hours + 1 0.25 18 +/- 2 + 2 0.55 24 +/- 3 + 3 0.20 36 +/- 4 + +There is one tug at the port. Tankers of all types require the services of this tug +to move into a berth, and later to move out of a berth. When the tug is available, +any berthing or de-berthing activity takes about one hour. Top priority is given to +the berthing activity. + +A shipper is considering bidding on a contract to transport oil from the port to +the United Kingdom. He has determined that 5 tankers of a particular type would +have to be committed to this task to meet contract specifications. These tankers +would require 21 +/- 3 hours to load oil at the port. After loading and de-berthing, +they would travel to the United Kingdom, offload the oil, and return to the port for +reloading. Their round-trip travel time, including offloading, is estimated to be +240 +/- hours. + +A complicated factor is that the port experiences storms. The time between +the onset of storms is exponentially distributed with a mean of 48 hours and a. +storm lasts 4 +/- 2 hours. No tug can start an operation until a storm is over. + +Before the port authorities can commit themselves to accommodating the +proposed 5 tankers, the effect of the additional port traffic on the in-port residence +time of the current port users must be determined. It is desired to simulate the +operation of the port for a one-year period (= 8640 hours) under the proposed new +commitment to measure in-port residence time of the proposed additional tankers, +as well as the three types of tankers which already use the port. All durations +given as ranges are uniformly distributed. + +[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/QuarryOperations/Experiment.hs b/examples/QuarryOperations/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/QuarryOperations/Experiment.hs @@ -0,0 +1,93 @@ + +module Experiment(experiment, generators) where + +import Control.Category +import Data.Monoid + +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 = 480.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 1000, + -- experimentRunCount = 10, + experimentTitle = "Quarry Operations" } + +shovelQueue = T.Queue $ resultByName "shovelQueue" +crusherQueue = T.Queue $ resultByName "crusherQueue" + +shovelActvty = T.Activity $ resultByName "shovelActvty" +crusherActvty = T.Activity $ resultByName "crusherActvty" + +shovelQueueCount = T.tr $ T.queueCount shovelQueue +shovelQueueCountStats = T.tr $ T.queueCountStats shovelQueue +shovelQueueWaitTime = T.tr $ T.queueWaitTime shovelQueue +shovelQueueRate = T.tr $ T.queueRate shovelQueue + +crusherQueueCount = T.tr $ T.queueCount crusherQueue +crusherQueueCountStats = T.tr $ T.queueCountStats crusherQueue +crusherQueueWaitTime = T.tr $ T.queueWaitTime crusherQueue +crusherQueueRate = T.tr $ T.queueRate crusherQueue + +shovelUtilisationFactor = T.tr $ T.activityUtilisationFactor shovelActvty +crusherUtilisationFactor = T.tr $ T.activityUtilisationFactor crusherActvty + +subgenerators1 :: ChartRendering r => String -> ResultTransform -> [WebPageGenerator r] +subgenerators1 title series = + [outputView $ defaultDeviationChartView { + deviationChartTitle = title ++ " (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = series }, + outputView $ defaultFinalHistogramView { + finalHistogramTitle = title ++ " (histogram)", + finalHistogramWidth = 1000, + finalHistogramSeries = series }, + outputView $ defaultFinalStatsView { + finalStatsTitle = title ++ " (statistics)", + finalStatsSeries = series } ] + +subgenerators2 :: ChartRendering r => String -> ResultTransform -> [WebPageGenerator r] +subgenerators2 title series = + [outputView $ defaultDeviationChartView { + deviationChartTitle = title ++ " (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = series }, + outputView $ defaultFinalStatsView { + finalStatsTitle = title ++ " (statistics)", + finalStatsSeries = series } ] + +subgenerators3 :: ChartRendering r => String -> ResultTransform -> ResultTransform -> [WebPageGenerator r] +subgenerators3 title series1 series2 = + [outputView $ defaultDeviationChartView { + deviationChartTitle = title ++ " (chart)", + deviationChartWidth = 1000, + deviationChartRightYSeries = series1 <> series2 }, + outputView $ defaultFinalStatsView { + finalStatsTitle = title ++ " (statistics)", + finalStatsSeries = series2 } ] + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView] <> + subgenerators3 "The shovel queue size" shovelQueueCount shovelQueueCountStats <> + subgenerators2 "The shovel queue wait time" shovelQueueWaitTime <> + subgenerators1 "The shovel queue rate" shovelQueueRate <> + subgenerators3 "The crusher queue size" crusherQueueCount crusherQueueCountStats <> + subgenerators2 "The crusher queue wait time" crusherQueueWaitTime <> + subgenerators1 "The crusher queue rate" crusherQueueRate <> + subgenerators1 "The shovel utilisation factor" shovelUtilisationFactor <> + subgenerators1 "The crusher utilisation factor" crusherUtilisationFactor diff --git a/examples/QuarryOperations/MainUsingCairo.hs b/examples/QuarryOperations/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/QuarryOperations/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/QuarryOperations/MainUsingDiagrams.hs b/examples/QuarryOperations/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/QuarryOperations/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/QuarryOperations/Model.hs b/examples/QuarryOperations/Model.hs new file mode 100644 --- /dev/null +++ b/examples/QuarryOperations/Model.hs @@ -0,0 +1,209 @@ + +{-# LANGUAGE Arrows #-} + +-- 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. + +module Model(model) where + +import Control.Monad +import Control.Monad.Trans +import Control.Category + +import Simulation.Aivika +import qualified Simulation.Aivika.Queue.Infinite as IQ + +-- | 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 Results +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] diff --git a/examples/QuarryOperations/README b/examples/QuarryOperations/README new file mode 100644 --- /dev/null +++ b/examples/QuarryOperations/README @@ -0,0 +1,25 @@ + +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. diff --git a/examples/SingleLaneTraffic/Experiment.hs b/examples/SingleLaneTraffic/Experiment.hs new file mode 100644 --- /dev/null +++ b/examples/SingleLaneTraffic/Experiment.hs @@ -0,0 +1,70 @@ + +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 = 3600.0, + spcDT = 0.1, + spcMethod = RungeKutta4, + spcGeneratorType = SimpleGenerator } + +-- | The experiment. +experiment :: Experiment +experiment = + defaultExperiment { + experimentSpecs = specs, + experimentRunCount = 1000, + -- experimentRunCount = 10, + experimentTitle = "Single-Lane Traffic Analysis" } + +waitTime = resultByName "waitTime" +greenLightTime = resultByName "greenLightTime" + +start = T.Resource $ resultByName "start" +startQueueCount = T.tr $ T.resourceQueueCount start +startQueueCountStats = T.tr $ T.resourceQueueCountStats start +startWaitTime = T.tr $ T.resourceWaitTime start +startCountStats = T.tr $ T.resourceCountStats start +startUtilisationCountStats = T.tr $ T.resourceUtilisationCountStats start + +generators :: ChartRendering r => [WebPageGenerator r] +generators = + [outputView defaultExperimentSpecsView, + outputView defaultInfoView, + outputView $ defaultFinalStatsView { + finalStatsTitle = "Green Light Time (Initial Conditions)", + finalStatsSeries = greenLightTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Average Waiting Time", + finalStatsSeries = waitTime }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Average Waiting Time Chart", + deviationChartWidth = 1000, + deviationChartRightYSeries = waitTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Queue Count", + finalStatsSeries = startQueueCountStats }, + outputView $ defaultDeviationChartView { + deviationChartTitle = "The Resource Queue Count Chart", + deviationChartWidth = 1000, + deviationChartRightYSeries = + startQueueCount <> startQueueCountStats }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Wait Time", + finalStatsSeries = startWaitTime }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Utilisation Summary", + finalStatsSeries = startUtilisationCountStats }, + outputView $ defaultFinalStatsView { + finalStatsTitle = "The Resource Availability Summary", + finalStatsSeries = startCountStats } ] diff --git a/examples/SingleLaneTraffic/MainUsingCairo.hs b/examples/SingleLaneTraffic/MainUsingCairo.hs new file mode 100644 --- /dev/null +++ b/examples/SingleLaneTraffic/MainUsingCairo.hs @@ -0,0 +1,15 @@ + +-- 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 = do + runExperiment experiment generators (WebPageRenderer $ CairoRenderer PNG) model1 + runExperiment experiment generators (WebPageRenderer $ CairoRenderer PNG) model2 + runExperiment experiment generators (WebPageRenderer $ CairoRenderer PNG) model3 diff --git a/examples/SingleLaneTraffic/MainUsingDiagrams.hs b/examples/SingleLaneTraffic/MainUsingDiagrams.hs new file mode 100644 --- /dev/null +++ b/examples/SingleLaneTraffic/MainUsingDiagrams.hs @@ -0,0 +1,17 @@ + +-- 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 = do + runExperiment experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model1 + runExperiment experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model2 + runExperiment experiment generators (WebPageRenderer $ DiagramsRenderer SVG M.empty) model3 diff --git a/examples/SingleLaneTraffic/Model.hs b/examples/SingleLaneTraffic/Model.hs new file mode 100644 --- /dev/null +++ b/examples/SingleLaneTraffic/Model.hs @@ -0,0 +1,136 @@ + +-- Example: Single-Lane Traffic Analysis +-- +-- It is described in different sources [1, 2]. So, this is chapter 15 of [2] and section 6.18 of [1]. +-- +-- The system to be modeled in this example consists of the traffic flow from +-- two directions along a two-lane road, one lane of which has been closed for +-- 500 meters for repairs. Traffic lights have been placed at each end of +-- the closed lane to control the flow of traffic through the repair section. +-- The lights allow traffic to flow for a specified time interval from only +-- one direction. When a light turns green, the waiting cars start and pass +-- the light every two seconds. If a car arrives at a green light when there +-- are no waiting cars, the car passes through the light without delay. The car +-- arrival pattern is exponentially distributed, with an average of 9 seconds +-- between cars from direction 1 and 12 seconds between cars from direction 2. +-- A light cycle consists of green in direction 1, both red, green in direction 2, +-- both red, and then the cycle is repeated. Both lights remain red for 55 seconds +-- to allow the cars in transit to leave the repair section before traffic from +-- the other direction can be initiated. +-- +-- The objective is to simulate the above system to determine values for +-- the green time for direction 1 and the green time for direction 2 which +-- yield a low average waiting time for all cars. +-- +-- [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 (model1, model2, model3) where + +import Control.Monad +import Control.Monad.Trans +import Control.Arrow + +import Data.Array + +import Simulation.Aivika +import qualified Simulation.Aivika.Resource as R + +data LightTime = + LightTime { greenLightTime1 :: Double, + greenLightTime2 :: Double } + +model :: LightTime -> Simulation Results +model lightTime = do + let greenLightTime = + array (1, 2) + [(1, return $ greenLightTime1 lightTime :: Event Double), + (2, return $ greenLightTime2 lightTime :: Event Double)] + waitTime1 <- newRef emptySamplingStats + waitTime2 <- newRef emptySamplingStats + let waitTime = + array (1, 2) [(1, waitTime1), (2, waitTime2)] + start1 <- + runEventInStartTime $ + R.newFCFSResource 1 + start2 <- + runEventInStartTime $ + R.newFCFSResource 1 + let start = + array (1, 2) [(1, start1), (2, start2)] + light1 <- newGateClosed + light2 <- newGateClosed + let stream1 = randomExponentialStream 9 + stream2 = randomExponentialStream 12 + runProcessInStartTime $ + flip consumeStream stream1 $ \x -> + liftEvent $ + runProcess $ + do R.requestResource start1 + awaitGateOpened light1 + t <- liftDynamics time + liftEvent $ + modifyRef waitTime1 $ + addSamplingStats (t - arrivalTime x) + when (t > arrivalTime x) $ + holdProcess 2 + R.releaseResource start1 + runProcessInStartTime $ + flip consumeStream stream2 $ \x -> + liftEvent $ + runProcess $ + do R.requestResource start2 + awaitGateOpened light2 + t <- liftDynamics time + liftEvent $ + modifyRef waitTime2 $ + addSamplingStats (t - arrivalTime x) + when (t > arrivalTime x) $ + holdProcess 2 + R.releaseResource start2 + let lighting = + do holdProcess 55 + liftEvent $ + openGate light1 + holdProcess $ + greenLightTime1 lightTime + liftEvent $ + closeGate light1 + holdProcess 55 + liftEvent $ + openGate light2 + holdProcess $ + greenLightTime2 lightTime + liftEvent $ + closeGate light2 + lighting + runProcessInStartTime lighting + return $ + results + [resultSource + "start" "Start Resource" + start, + -- + resultSource + "waitTime" "Wait Time" + waitTime, + -- + resultSource + "greenLightTime" "Green Light Time" + greenLightTime] + +modelSummary :: LightTime -> Simulation Results +modelSummary lightTime = + fmap resultSummary $ model lightTime + +lightTime1 = LightTime 60 45 +lightTime2 = LightTime 80 60 +lightTime3 = LightTime 40 30 + +model1 = model lightTime1 +model2 = model lightTime2 +model3 = model lightTime3 + +modelSummary1 = fmap resultSummary model1 +modelSummary2 = fmap resultSummary model2 +modelSummary3 = fmap resultSummary model3 diff --git a/examples/SingleLaneTraffic/README b/examples/SingleLaneTraffic/README new file mode 100644 --- /dev/null +++ b/examples/SingleLaneTraffic/README @@ -0,0 +1,26 @@ + +Example: Single-Lane Traffic Analysis + +It is described in different sources [1, 2]. So, this is chapter 15 of [2] and section 6.18 of [1]. + +The system to be modeled in this example consists of the traffic flow from +two directions along a two-lane road, one lane of which has been closed for +500 meters for repairs. Traffic lights have been placed at each end of +the closed lane to control the flow of traffic through the repair section. +The lights allow traffic to flow for a specified time interval from only +one direction. When a light turns green, the waiting cars start and pass +the light every two seconds. If a car arrives at a green light when there +are no waiting cars, the car passes through the light without delay. The car +arrival pattern is exponentially distributed, with an average of 9 seconds +between cars from direction 1 and 12 seconds between cars from direction 2. +A light cycle consists of green in direction 1, both red, green in direction 2, +both red, and then the cycle is repeated. Both lights remain red for 55 seconds +to allow the cars in transit to leave the repair section before traffic from +the other direction can be initiated. + +The objective is to simulate the above system to determine values for +the green time for direction 1 and the green time for direction 2 which +yield a low average waiting time for all cars. + +[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