Package jline.solvers.ldes
Class LDESResult
java.lang.Object
jline.solvers.SolverResult
jline.solvers.ldes.LDESResult
- Since:
- 1.0
- Author:
- QORE Lab, Imperial College London
- See Also:
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Field Summary
FieldsModifier and TypeFieldDescriptionConfidence interval half-widths for arrival rates [stations x classes]Average orbit size (time-weighted mean jobs in orbit) [stations x classes]Average wait time before reneging [stations x classes]Steady-state expected Markov reward per reward name, E[r] = (1/T) integral r(X(t)) dt.Number of customers who balked (refused to join upon arrival) [stations x classes]Balking probability (balked / arrivals) [stations x classes]booleanFlag indicating whether the simulation converged before reaching max events/timeintNumber of batches used for final confidence interval estimationPassage time samples for empirical CDF computation [stations][classes].Confidence interval half-widths for queue lengths [stations x classes]Relative precision achieved for queue lengths (CI half-width / mean) [stations x classes]Number of samples (observations) used for queue length estimation [stations x classes]Number of customers who reneged (abandoned queue due to expired patience) [stations x classes]Reneging rate (reneged / (completed + reneged + dropped)) [stations x classes]Response time samples for empirical CDF computation [stations][classes].Number of customers dropped after exceeding max retrial attempts [stations x classes]Number of successful retrial attempts (customers who re-entered queue from orbit) [stations x classes]Names of the reward functions, in registration order.Time points associated withtranReward.Confidence interval half-widths for response times [stations x classes]Relative precision achieved for response times (CI half-width / mean) [stations x classes]Number of samples (observations) used for response time estimation [stations x classes]Network structure used for the analysisExact joint-state residence-time histogram (populated whenLDESOptions.exportStateHistogramis set).Residence time per state instateHistogramSpace(column vector).Integer joint-state trajectory (one aggregated state per row, same layout asstateHistogramSpace) sampled along the simulated path, downsampled to a bounded number of points.Time points associated withstateTrajectorySpace(column vector).Stopping reason: "convergence", "max_events" (service-completion budget, options.samples/events, reached), "max_sim_events" (all-event cap, LDESOptions.maxSimEvents, reached), or "max_time" (wall-clock budget).Confidence interval half-widths for throughputs [stations x classes]Relative precision achieved for throughputs (CI half-width / mean) [stations x classes]Number of samples (observations) used for throughput estimation [stations x classes]longTotal number of simulated service completion eventsTransient aggregated state probabilities per node [nodeIdx] -> [numTimePoints x numAggrStates].Transient aggregated state space per node [nodeIdx] -> [numAggrStates x numClasses].Transient state probabilities over time [numTimePoints x numStates].Transient state space matrix [numStates x stateVectorLength].Time points for transient probability analysis.Single-run transient reward trajectory r(X(t)) per reward name.Transient synchronization matrix for multi-class coordinationTransient system state matrices indexed by time pointsConfidence interval half-widths for utilizations [stations x classes]Relative precision achieved for utilizations (CI half-width / mean) [stations x classes]Number of samples (observations) used for utilization estimation [stations x classes]Variance reduction method used during simulation.Confidence interval half-widths for residence times [stations x classes] -
Constructor Summary
ConstructorsConstructorDescriptionConstructs an empty LDESResult to allow field population from different sources.LDESResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer, Matrix> tranSysState, Matrix tranSync, NetworkStruct sn) Constructs a LDESResult with the specified performance metrics and state information. -
Method Summary
Modifier and TypeMethodDescriptionvoidinitRespTimeSamples(int nStations, int nClasses) Initializes the respTimeSamples array with empty lists for each (station, class) pair.Methods inherited from class jline.solvers.SolverResult
deepCopy, reset
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Field Details
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tranSysState
Transient system state matrices indexed by time points -
tranSync
Transient synchronization matrix for multi-class coordination -
sn
Network structure used for the analysis -
QNCI
Confidence interval half-widths for queue lengths [stations x classes] -
UNCI
Confidence interval half-widths for utilizations [stations x classes] -
RNCI
Confidence interval half-widths for response times [stations x classes] -
TNCI
Confidence interval half-widths for throughputs [stations x classes] -
ANCI
Confidence interval half-widths for arrival rates [stations x classes] -
WNCI
Confidence interval half-widths for residence times [stations x classes] -
varianceReductionMethod
Variance reduction method used during simulation. Values: "none" (default), "antithetic", "control", "both" - "none": Standard simulation without variance reduction - "antithetic": Antithetic variates using synchronized 1-U method - "control": Control variates using mean-based correction - "both": Combined antithetic and control variates -
converged
public boolean convergedFlag indicating whether the simulation converged before reaching max events/time -
stoppingReason
Stopping reason: "convergence", "max_events" (service-completion budget, options.samples/events, reached), "max_sim_events" (all-event cap, LDESOptions.maxSimEvents, reached), or "max_time" (wall-clock budget). -
convergenceBatches
public int convergenceBatchesNumber of batches used for final confidence interval estimation -
totalSimulatedEvents
public long totalSimulatedEventsTotal number of simulated service completion events -
QNSamples
Number of samples (observations) used for queue length estimation [stations x classes] -
UNSamples
Number of samples (observations) used for utilization estimation [stations x classes] -
RNSamples
Number of samples (observations) used for response time estimation [stations x classes] -
TNSamples
Number of samples (observations) used for throughput estimation [stations x classes] -
QNRelPrec
Relative precision achieved for queue lengths (CI half-width / mean) [stations x classes] -
UNRelPrec
Relative precision achieved for utilizations (CI half-width / mean) [stations x classes] -
RNRelPrec
Relative precision achieved for response times (CI half-width / mean) [stations x classes] -
TNRelPrec
Relative precision achieved for throughputs (CI half-width / mean) [stations x classes] -
renegedCustomers
Number of customers who reneged (abandoned queue due to expired patience) [stations x classes] -
avgRenegingWaitTime
Average wait time before reneging [stations x classes] -
renegingRate
Reneging rate (reneged / (completed + reneged + dropped)) [stations x classes] -
balkedCustomers
Number of customers who balked (refused to join upon arrival) [stations x classes] -
balkingProbability
Balking probability (balked / arrivals) [stations x classes] -
retriedCustomers
Number of successful retrial attempts (customers who re-entered queue from orbit) [stations x classes] -
retrialDropped
Number of customers dropped after exceeding max retrial attempts [stations x classes] -
avgOrbitSize
Average orbit size (time-weighted mean jobs in orbit) [stations x classes] -
respTimeSamples
Response time samples for empirical CDF computation [stations][classes]. Each element is a list of individual response time observations. -
passTimeSamples
Passage time samples for empirical CDF computation [stations][classes]. Passage times track time from arrival to departure including routing delays. -
tranProbT
Time points for transient probability analysis. -
tranProbPit
Transient state probabilities over time [numTimePoints x numStates]. Each row contains probability distribution at that time point. -
tranProbStateSpace
Transient state space matrix [numStates x stateVectorLength]. Defines the state corresponding to each column in tranProbPit. -
tranProbAggrPit
Transient aggregated state probabilities per node [nodeIdx] -> [numTimePoints x numAggrStates]. -
tranProbAggrStateSpace
Transient aggregated state space per node [nodeIdx] -> [numAggrStates x numClasses]. -
avgReward
Steady-state expected Markov reward per reward name, E[r] = (1/T) integral r(X(t)) dt. Populated only when the model defines rewards via model.setReward. -
tranReward
Single-run transient reward trajectory r(X(t)) per reward name. -
rewardTime
Time points associated withtranReward. -
rewardNames
Names of the reward functions, in registration order. -
stateHistogramSpace
Exact joint-state residence-time histogram (populated whenLDESOptions.exportStateHistogramis set). Each row is an aggregated system state in the CTMCstateSpaceAggrlayout (station-major, class-minor,nstations*nclassescolumns). -
stateHistogramTime
Residence time per state instateHistogramSpace(column vector). Divide by its sum to obtain steady-state state probabilities. -
stateTrajectorySpace
Integer joint-state trajectory (one aggregated state per row, same layout asstateHistogramSpace) sampled along the simulated path, downsampled to a bounded number of points. Used by MATLAB/native Python for getTranReward. -
stateTrajectoryTime
Time points associated withstateTrajectorySpace(column vector).
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Constructor Details
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LDESResult
public LDESResult()Constructs an empty LDESResult to allow field population from different sources. -
LDESResult
public LDESResult(Matrix QN, Matrix UN, Matrix RN, Matrix TN, Matrix CN, Matrix XN, Map<Integer, Matrix> tranSysState, Matrix tranSync, NetworkStruct sn) Constructs a LDESResult with the specified performance metrics and state information.- Parameters:
QN- queue lengths [stations x classes]UN- utilizations [stations x classes]RN- response times [stations x classes]TN- throughputs [stations x classes]CN- visit counts [stations x classes]XN- arrival rates [stations x classes]tranSysState- transient system states indexed by timetranSync- transient synchronization matrixsn- network structure information
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Method Details
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initRespTimeSamples
public void initRespTimeSamples(int nStations, int nClasses) Initializes the respTimeSamples array with empty lists for each (station, class) pair.- Parameters:
nStations- number of stationsnClasses- number of classes
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