Course Description
There are four classifications of models: discrete or continuous, probabilistic or deterministic, static or dynamic, and open loop or closed loop. The course objective is to produce students who are capable of modeling and simulating discrete, probabilistic, dynamic, and open loop system as well analyzing, verifying and validating the simulations results. The purpose of this course is to provide students with a theoretical base in discrete-event modeling and simulation for applying concepts related to computer networks and information system modeling (random numbers, Monte Carlo methods, Probabilistic modeling, Queuing theory models, Markov models and chains, arrival laws, service laws, birth-dead process, stochastic process, stationary process, stochastic analysis, networks analysis and routing algorithms, verification and validation of simulation models). Discrete production systems are studied (time flow mechanism, Petri nets). Students should complete a major project using simulation models and a standard simulation language. Students will be trained on some software tools such as: ARENA, QNAP, and PETRI NETS
Course ID: CS 515
Credit hours | Theory | Practical | Laboratory | Lecture | Studio | Contact hours | Pre-requisite | 3 | 2 | 1 | 3 | MATH 301 |
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