Introduction to Modeling and Simulation
Osman Balci

Learning Objectives
Modeling and Simulation (M&S) is a discipline (a branch of knowledge) consisting of many areas such as discrete M&S, continuous M&S, Monte Carlo M&S, Agentbased M&S, and System Dynamics M&S. M&S is used in almost all disciplines similar to how mathematics is used in other disciplines. M&S is a large and diverse discipline used to provide solutions to complex problems encountered in almost every field such as engineering, business, sciences (e.g., agricultural, biological, medical, social), military, and government.
Some universities offer B.S., M.S. and Ph.D. degree programs in M&S.
The purpose of this course is to provide a comprehensive introduction to M&S by focusing on Discrete M&S at undergraduate or graduate level. The course aims to teach a student how to conduct an M&S project from A to Z (i.e., throughout the entire M&S life cycle) and to become a “solution provider” to complex problems by using M&S.
Having successfully completed this course, the student will be able to:
 solve a problem by way of using M&S,
 formulate a problem and specify requirements for an M&S application,
 develop a simulation conceptual model,
 architect a networkcentric M&S application,
 design and implement a Discrete M&S application,
 participate in any M&S project with the title of M&S Engineer, and
 effectively manage an M&S project throughout its entire life cycle.
Description
The purpose of this course is to teach the fundamentals of Modeling and Simulation (M&S) with emphasis on discrete M&S. The course is taught based on an M&S life cycle (a blueprint for conducting an M&S project) developed by the instructor as applicable for any area of M&S. It covers the entire M&S life cycle and teaches how to conduct a largescale M&S project. The following topics are covered: M&S fundamentals, M&S life cycle, Verification and Validation (V&V) and Quality Assurance (QA) over the M&S life cycle. Problem Formulation. M&S Requirements Engineering. Simulation Conceptual Modeling. Architecting an M&S Application. Design of an M&S Application. Simulation Input Data Modeling. M&S Implementation / Programming. Random Number Generation. Random Variate Generation. Simulation Programming Conceptual Frameworks. M&S Application Integration. Experimentation with, Exercise or Use of an M&S Application. Presentation of M&S Project Results. Certification of an M&S Application. Storage of Certified M&S Applications. Feedback on Use of a Certified M&S Application. Principles of M&S V&V and QA. M&S Verification, Validation and Testing Techniques.
Prerequisites
 Ability to program the computer in a highlevel programming language such as Java, C, C++, C#, or Objective C.
 Basic knowledge of Probability and Statistics