When simulation is the appropriate tool and when it is not appropriate; Advantagesand disadvantages of Simulation; Areas of application; Systems and systemenvironment; Components of a system; Discrete and continuous systems; Model of a system;Types of Models; Discrete-Event System Simulation; Steps in a Simulation Study.
Review of terminology and concepts; Random Variables, Probability Distribution,Probability distribution function, Useful statistical models; Discrete distributions;Continuous distributions; Poisson process; Empirical distributions.
Properties of random numbers; Generation of pseudo-random numbers; Techniquesfor generating random numbers; Tests for Random Numbers, Random-Variate Generation:Inverse transform technique; Acceptance-Rejection technique; Special properties.
Characteristics of queuing systems; Queuing notation Simulation Examples: Queuing,Inventory System
Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-AdvanceAlgorithm, World Views, Manual simulation Using Event Scheduling; List processing.Simulation in Java;
Data Collection; Identifying the distribution with data; Parameter estimation; Goodness ofFit Tests; Fitting a non-stationary Poisson process; Selecting input models withoutdata; Multivariate and Time-Series input models, uniformity and independence, Chi-Squaretest, K-S Test.
Verification, Calibration, and Validation; Optimization: Model building, verification andvalidation; Verification of simulation models; Calibration and validation of models
Types of simulations with respect to output analysis; Stochastic nature of output data;Absolute measures of performance and their estimation; Output analysis for terminatingsimulations; Output analysis for steady-state simulations.