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Xiannong Meng Department of Computer Science University of Texas - Pan American
Last revised: July 1998
#./intro.tex#;'' Introduction When is Simulation the Appropriate Tool? Advantages and Disadvantages Systems and System Environment Components of a System Discrete and Continuous Systems Model of a System Types of Models Steps in a Simulation Study Simulation Examples Queueing Systems Simulation of Inventory Systems Other Examples of Simualtion General Principles Concepts and Definitions Execution Mechanism of Discrete-Event Driven Simulation World Views Other Examples Parallel Discrete Event Simulation Basics Conservative Approach Optimistic Mechanisms References Statistical Model of Simulation Review of Terminology and Concepts Useful Statistical Models Discrete Random Variables Contineous Distributions Queueing Models Characteristics Queue Bahavior and Queue Discipline Service Time and Service Mechanisms Queueing Notation Long Term Measures of Performance of Queueing Systems Markov Models and Its Evaluation Random-Number Generation Properties of Random Numbers Generation of Pseudo-Random Numbers Techniques for Generating Random Numbers Linear Congruential Method Combined Linear Congruential Generators Tests for Random Numbers Frequency test Runs Tests Tests for Auto-correlation Gap Test Poker Test Random Variate Generation Inverse Transform Technique Exponential Distribution Uniform Distribution Weibull Distribution Triangular Distribution Empirical Continuous Distributions Continuous Distributions without a Closed-Form Inverse Discrete Distribution Direct Transformation for the Normal Distribution Convolution Method Acceptance-Rejection Technique to Generate Random Variate Input Modeling Identifying the Distribution with Data Histograms Selecting the Family of Distribution Quantile-Quantile Plots Parameter Estimation Goodness-of-Fit Tests Verification and Validation of Simulation Models Model Buidling, Verification, and Validation Verification of Simulation Models Calibration and Validation of Models Face Validity Validation of Model Assumptions Validating Input-Output Transformations Input-Output Validation: Using Historical Input Data Output Analysis for a Single Model Stochastic Nature of Output Data Types of Simulations with Respect to Output Analysis Measures of Performance and Their Estimation Point Estimation Interval Estimation Output Analysis for Terminating Simulations Interval Estimate for a Fixed Number of Replications Interval Estimate with Specified Precision Output Analysis for Steady-State Simulations Initialization Bias in Steady-State Simulations Replication Method for Steady-State Simulations Sample Size in Steady-State Simulations Batch Means for Interval Estimation in Steady-State Simulations About this document ... Meng Xiannong 2002-10-18
