INDE 504 Discrete-Event Simulation – Spring 2025

Instructor: Bacel Maddah

Syllabus

Class Notes (over a tentative schedule)

Week 1   

OR and Simulation Modeling

Excel simulation for the game of Craps

Weeks 2-3

Probability and Random Variable Review

Queueing Primer

Weeks 4-5

 Introduction to Discrete Event Simulation. 

G/G/1 Hand Simulation. 

Monte Carlo and Process Oriented Simulation.  

Simulation Verification and Validation. 

Weeks 6-7

Input Analysis I:  Overview and data collection.  

Input Analysis II: Hypothesizing distribution and parameter estimation.  

 Understanding MLEs

Input Analysis III:  Goodness of fit, what to do with no data. 

Chi Square Test on Drive-through Inter-arrival data

Weeks 8-9

Random Number Generators (1): Overview, Linear Congruential Generators, Good and Common LCGs.    

 Random Number Generators (2):  Testing RNGs, Empirical Tests, Chi^2, KS, Runs.

Weeks 10-12

Generating random Varietes (1):  Inverse Transform, Composition, Convolution. 

Generating random Varietes (2):  Acceptance-Rejection, Uniform, Triangular, Normal, Lognormal,  Bernoulli, Binomial, and Geometric. 

Inverse Transform dot Excel 

Excel model for generating Z based on 12 Us

Generating random Varietes (3):  Empirical Distributions,  Stationary Poisson Process, Nonstationary Poisson.   

Excel Simulation of a Poisson Process

Simulating stock prices

Dell stock simulations

Weeks 13-14

Output Analysis 1:  Nature of Output, Transient and Steady States, Terminating / Nonterminating   Simulations, Estimating Means.   

Output Analysis 2:  Choosing Initial Conditions, Steady State Analysis,  Replication/Deletion, Batch Means, Comparing Two Configurations. 

Output Analysis 3:  Comparing > 2 Systems, Comparing with Standard, Variance Reduction, CRN, Antithetic Variates, Control Variates. 

Obtaining a Specific Precision of  Output dot Excel

Project

Sign-up and submission sheet

Project template (to be followed strictly on font size and type, line spacing, margins, page limit, etc.)

Python Stuff

Introduction to Python

Distribution fitting with Scipy

Weight-height data set 

Introduction to SimPy

Simulation with Simpy

Homework Assignments

HW 1.  Probability refresh.  Due Tuesday, February 4, in class. 

HW 2.   Discrete event and Monte Carlo by hand.   

HW 3.  KSZ book: 3-6, 3-7, 3-13, and supplement problem.  

HW 4.  BCNN book, Ch 9 (pp. 376-379): 9.7, 9.11, 9.12, 9.14, 9.17, 9.19 (use Arena Input Analyzer).  

HW 5.  BCNN book, Ch 7 (p. 293): 7.2, 7.4, 7.5, 7.6, and supplement problem.  

HW 6.  BCNN book, Ch 8 (use Excel RNG):  8.4, 8.5, 8.9, 8.29, Ch 11: 11.1, 11.4.  

Links

NN Taleb mini lectures in probability  

Flaw of averages video

Winter Simulation Conference archive

Model Thinking With Dr. Queue

The search for the random numbers that run our lives

The great German land lottery