# 22911 Simulation Modeling and Analysis

**Credits: **4 graduate credits in Computer Science

**Prerequisite**: Admission to the graduate program in Computer Science 1

The course is based on *Simulation Modeling and Analysis* (4th ed.), by A.M. Law (McGraw Hill, 2007); and on *Simulation with Arena* (5th ed.), by W.D. Kelton, R.P. Sadowski, and D.A. Sadowski (McGraw Hill, 2010).

Simulation modeling is an important tool for systems analysis by building a mathematical model of the system and simulating system performance using the model. The simulation model is primarily useful for analyzing and estimating the performance of complex stochastic systems which are difficult or impossible to analyze analytically, or in cases where testing the system itself is expensive or unfeasible.

Simulation studies include several steps: stating the problem and defining the system boundaries, building a model to represent the system, generating random numbers and variates, designing simulation experiments, performing experiments using simulation software, verifying and validating the simulation model, analyzing outputs and drawing conclusions. Simulations are used in many fields. In computer science, simulations are used in the area of research as well as in applications such as analysis of communication protocols, routing algorithm analysis, computer resource allocation.

The course discusses theoretical topics relating to model design and discrete event simulation models. Students also experience building a simulation model using Arena software.

1Students who have not fulfilled this requirement may, under certain circumstances, enroll in this course.