Fundamental concepts in modelling and simulation are explored in this course. An applied approach using practical examples will strengthen the techniques learned. Topics include: Statistical background for simulation; system reliability; mathematical description of general dynamic systems; discrete event; discrete time and continuous time; queuing models; effects of queue disciplines; factors affecting queue systems; implementation and management of models; performance evaluation of models; simulation languages; SLAM. Students entering the course should have a strong grasp of a high level programming language.

Course Type | Major |
---|---|

Credit Hour | 3 |

Lecture Hour | 45 |

- Differentiate between dynamic and static models, discrete event and continuous-time systems.
- Define, explain, and discuss the fundamental elements of discrete-event simulation including analytical elements, random processes, random variates, and inputs to simulation.
- Analyse a real world problem, and apply modelling methodologies to develop a discrete-event simulation model.
- Interpret and contrast discrete-event techniques for implementing a solution to a simulation problem.

*Simulation Modeling and Analysis (3rd Edition)*by Law and Kelton*Computer Simulation and Modelling*by Francis Neelamkavil*Discrete-Event System Simulation (5th edition)*by Jerry Banks, John Carson, Barry L. Nelson, David Nicol

Biweekly Quiz, One Midterm Exam, One Final Exam, Project

Letter Grade | Marks | Grade Point |
---|---|---|

A | 90 - 100 | 4.00 |

A- | 85 - 89 | 3.70 |

B+ | 80 - 84 | 3.30 |

B | 75 - 79 | 3.00 |

B- | 70 - 74 | 2.70 |

C+ | 65 - 69 | 2.30 |

C | 60 - 64 | 2.00 |

C- | 55 - 59 | 1.70 |

D+ | 50 - 54 | 1.30 |

D | 45 - 49 | 4.00 |

F | 00 - 44 | 4.00 |