CS-346-546 Simulation Modeling and Analysis

Mathematics, Statistics & Computer Science Department

COURSE NO./TITLE: CS-346/546 (354-546) Simulation Modeling & Analysis


COURSE DESCRIPTION: Simulation as a problem solving technique; models, analysis and languages for simulation; data collection; random variate generation; verification and validation; output analysis; optimization of systems.

Prerequisites: CS-244, STAT-332


  • Simulation with Visual Slam and Awesim, 1st, by Pritsker
  • Simulation Modeling & Analysis, 3rd Ed. by Law (adopted Spring 2004)

COURSE OBJECTIVES: Upon completion of this course a student should be able to:

  1. Understand how simulation modeling can be utilized in solving various real world problems and improving the performance of existing systems..
  2. Identify which problems are best suited to simulation modeling.
  3. Design and implement a system model using a simulation language, as well as select the appropriate analysis method.
  4. Understand the randomness in a system and how to model it..
  5. Demonstrate their ability to solve real-life problems by using simulation.
  6. Realize the importance of using input and output analysis of simulation models. Graduate students should further be able to:
  7. Demonstrate a broader understanding of the theoretical aspects and basics of simulation modeling, by developing two large simulation projects.


  1. Basic Simulation Modeling
  2. Modeling Complex System
  3. Simulation Languages for Modeling
  4. Valid and Credible Simulation Models
  5. Data Collection and Analysis
  6. Random-Numbers and Random-Variate Generation
  7. Output Data Analysis
  8. Simulation (Model Experimentation) and Optimization

Revised 6/08