Statistical Output Analysis for Terminating Simulations

Terminating Simulations

Simulations with specific starting and stopping conditions.

Steady-State Simulations

Simulations run indefinitely; initial conditions irrelevant.

Random Input Random Output (RIRO)

Random inputs lead to unpredictable simulation outputs.

Statistical Analysis

Evaluating output data for precision and variability.

IID Replications

Independent and identically distributed simulation runs.

Replication Parameters

Settings to define number of simulation replications.

Category Overview Report

Summary report with statistical analysis of outputs.

Confidence Intervals

Range estimating expected values with specified probability.

Half Width

Half the width of a confidence interval.

Sample Standard Deviation (s)

Measure of output variability from sample data.

Normal Critical Value (z)

Value from standard normal distribution for confidence levels.

Sequential Sampling

Sampling method adjusting based on previous results.

Batch Run

Running simulations without animation for efficiency.

Expected Value

Average outcome from an infinite number of replications.

Prediction Interval

Range predicting where future data points will fall.

Central Limit Theorem

Distribution of sample means approaches normality with large samples.

Cross-Replication Variability

Variability observed between different replications of a model.

OptQuest

Tool for searching optimal scenarios in simulations.

Model Configuration

Specific setup or arrangement of simulation parameters.

Statistical Output Analysis

Evaluating results from simulation runs for insights.

Sensitivity Analysis

Assessing how output changes with varying input parameters.

Simulation Runs

Execution of a model to generate output data.

Output Analyzer

Tool for visualizing and analyzing simulation results.

Total Cost.dat

File for storing total cost statistics in simulations.

Percent Rejected

Measure of rejected outputs in simulation scenarios.

Base Case

Scenario with original inputs, no additional resources.

More-Resources Case

Scenario with added trunk lines and new technologies.

Expressions

Values saved from Statistic data module in Arena.

Binary .dat Files

File format readable only by Output Analyzer.

Data Group

Collection of .dat files for analysis in Output Analyzer.

Compare Means

Statistical method to evaluate differences between scenarios.

Paired-t Test

Statistical test for comparing two related samples.

Process Analyzer (PAN)

Tool for managing multiple simulation scenarios efficiently.

Scenario in PAN

Combination of program file, input controls, and responses.

Project in PAN

Collection of scenarios, can be saved as .pan file.

Output Responses

Values collected from simulation outputs for analysis.

Controls in PAN

Input parameters that can be adjusted in scenarios.

Designed Experiment

Structured study of control effects and interactions.

Statistical Conclusion

Inference drawn from statistical analysis of outputs.

Output File Column

Column in Statistic module for specifying output files.

Lumped Replications

Combining multiple replications for statistical analysis.

Scenario Properties

Dialog for defining scenario parameters in PAN.

Confidence Level

Probability that the confidence interval contains the true parameter.

Experimental Scenarios

Non-base-case scenarios for resource allocation analysis.

Resource Allocation

Distribution of additional funds to specific resources.

Trunk Lines

Communication lines, cost $98 each.

Tech-Support Personnel

Employees providing technical assistance; various costs.

Sales Personnel

Employees responsible for sales; cost $340 each.

PAN Scenarios

Different experimental setups in simulation analysis.

Statistical Validity

Ensures accurate comparisons of simulation results.

Total Cost Column

Data column used for cost analysis in scenarios.

Box and Whisker Chart

Visual representation of data distribution and variability.

Error Tolerance

Acceptable margin of error in scenario evaluations.

Objective Function

Output to minimize in optimization problems.

Constraints

Limits placed on input control variables.

Feasible Scenarios

Possible configurations within defined constraints.

Heuristic Algorithms

Methods for problem-solving using practical approaches.

Stopping Criteria

Conditions under which the optimization process halts.

Replication Length

Duration for running each simulation instance.

Integer Controls

Discrete variables with specific lower and upper bounds.

Running Optimization

Initiating the optimization process in OptQuest.

Scenario Evaluation

Assessment of different configurations for effectiveness.

Best Scenario Identification

Process of determining the most effective configuration.

Simulation Model Output

Results generated from running a simulation model.

Resource Combinations

Various ways to allocate resources in scenarios.

Data Logging

Recording results of all scenarios for analysis.

Scenario Duplication

Creating copies of scenarios for further experimentation.

Simulation Execution

Running selected scenarios to gather results.