- COURSE NUMBER AND CREDIT
CSC 454 - 3 Semester Hours
- COURSE TITLE
System Simulation and Modeling
- COURSE DESCRIPTION
Simulation, modeling and problem-solving techniques;
discrete event and continuous change models;
simulation languages; simulation applications.
CSC 241, MAT 215 and at least one upper-level programming course.
- COURSE JUSTIFICATION
The course provides students with the basic knowledge
and experience necessary to utilize computer
simulation as a tool for system modeling and problem solving. The
technical aspects of constructing and analyzing a
simulation model will be discussed, along with the
implementing the basic components of a discrete-event simulator.
The students will be exposed to a wide variety of
computer simulation applications.
- COURSE OBJECTIVES
Upon successful completion of this course, students will be able to:
- demonstrate proficiency in modeling a real-life system, including data gathering,
input and output analysis.
- write a discrete-event simulator.
- COURSE OUTLINE
- Continuous Time Simulation
- Examples of Physical Systems
- Approximation by Finite Differences
- Introduction to Discrete-Event System Simulation
- Simulation examples: queueing and inventory systems
- Concepts discrete-event simulation: event list, event-scheduling, and
time advance algorithms
- Statistical Models in Simulation
- Discrete and continuous distributions
- Poisson process
- Empirical distributions
- Useful statistical models
- Queueing Models
- Characteristics of queueing systems and queueing notation
- Long-run measurements of performance
- Steady state behaviors of infinite- and finite-population models
- Random Numbers
- Properties of random number generators
- Techniques for generation of pseudo-random numbers
- Tests for random numbers
- Random Variate Generation
- Inverse Transform technique
- Direct transformation for the normal and lognormal distributions
- Convolution method
- Acceptance-rejection technique
- Analysis of Simulation Data
- Input modeling: data collection, identification of the distribution,
parameter estimation, goodness-of-fit tests.
- Verification and validation of simulation models: model building, verification,
calibration and validation of models.
- Output analysis: measures of performance and their estimation, terminating and
- METHODS OF INSTRUCTION
- COURSE REQUIREMENTS
Assigned readings, homework, papers, programs, and projects.
- MEANS OF EVALUATION
- Homework, exams, programming assignments, programming project, modeling project
No additional resources needed.
J. Banks (ed).
Handbook of Simulation: Principles, Methodology, Advances, Applications,
J. Banks, J.S. Carson, II, B.L. Nelson and D.M. Nicol.
Discrete-Event System Simulation.
C. Hanell, B.K. Ghosh and R Bowden.
Simulation Using ProModel.
W.D. Kelton, R.P.Sadowski and D.A. Sadowski.
Simulation with Arena.
A.M. Law and W.D. Kelton.
Simulation Modeling and Analysis, (3rd ed).
Simulation: A Modeler's Approach.
John Wiley and Sons,