Modeling and Simulation Course Overview

This simulation course is designed for operations research analysts, systems analysts, military planners, engineers, computer scientists, and technical managers who would like to use simulation to design and optimize real-world systems. It encompasses a full spectrum of applications, including defense, manufacturing, transportation, communications networks, healthcare, process reengineering, call centers, supply chains, and services. The course presents definitive methods for developing a simulation model, ensuring its validity, choosing simulation software, selecting input probability distributions, analyzing simulation runs, and project management. A case study illustrates the step-by-step application of simulation-modeling techniques. Students will have an opportunity to analyze simulation input and output data in class. The prerequisite for this seminar is a basic course in statistics, or the equivalent.

Versions of this seminar have been given for organizations such as Boeing, Coca-Cola, GM, Hewlett-Packard, IBM, Lockheed Martin, Los Alamos National Lab, NASA, NATO (Netherlands), NSA, Sasol Technology (South Africa), U.S. Air Force, U.S. Army, and U.S. Navy.

Outline

Each Attendee Will Receive the Following:

  • The book Simulation Modeling and Analysis (4th Edition) by Averill M. Law – widely considered to be the “bible” of simulation with more than 144,500 copies in print
  • An opportunity to talk to Dr. Law on a one-to-one basis about your particular applications

What You Will Learn:

  1. Designing and Optimizing Systems via Simulation Modeling
  2. Selecting Simulation Software
  3. Building Valid, Credible, and Appropriately Detailed Simulation Models
  4. Modeling Randomness in Real-World Systems
  5. Reaching Correct Decisions from Simulation Output Data
  6. Case Study
  7. 22 Critical Pitfalls in Simulation Modeling and How to Avoid Them

Critical Questions That the Seminar Will Answer:

  • What is a definitive overall approach for conducting a simulation study?
  • How do you determine the best simulation software for your application?
  • How do you decide on an appropriate level of model detail?
  • What are the proven techniques for ensuring model validity and credibility?
  • How can you accurately model the randomness in your system?
  • How can you determine the correct length of a simulation run?
  • What are 22 critical pitfalls in simulation modeling and how can they be avoided?