Faculdade de Ciências e Tecnologia




Academic unit

Faculdade de Ciências e Tecnologia


Departamento de Engenharia Mecânica e Industrial



Teacher in charge

Ana Paula Ferreira Barroso, Virgílio António Cruz Machado

Weekly hours


Total hours


Teaching language



The course aims to provide students with knowledge on methodologies, models and techniques for discrete simulation. As a means to assist students in systems modeling and its simulation it is used the Arena software. This course therefore has a strong practical component of formulation, modeling and solving problems in the laboratory, being used computers. The adequate modeling of a system allows to make the simulation of its operation, in a virtual environment, and to evaluate their performance considering different scenarios and different management policies.

It is intended that at the end of the course students have acquired the skills to simulate part of an operations management system by building a mathematical model that comes as close as possible to representing the reality of the system. Additionally it is intended to develop skills that allow them to select the methodologies and techniques appropriate to the particular system both with respect to the modeling and the analysis of the results of the simulation.

It is intended also that students are able to develop a critical sense regarding the system performance obtained from the simulation results analysis.

Subject matter

Introduction and fundamental simulation concepts
Simulation model components
How to develop a simulation model
How to develop a simulation study
Randomness of simulation system output
Replication of the simulation output
Introduction to Arena Software
Building a simple system using Arena software
Modeling basic operations
Input: Statistical issues
Input modeling. Fitting input distributions via the Input Analyzer
Nonstationary arrival processes
Modeling detailed operations
Statistical analysis of output from Terminating simulations
Statistical analysis of output from Steady-State simulations
Statistical issues of simulation
Random-number generation and variance reduction


Law A.M. e Kelton W.D. (2007) Simulation Modeling and Analysis, McGraw-Hill International Edition, New York.

Kelton W.D., Sadowski R.P. e Swets N.B. (2009) Simulation with ARENA (5ª ed.), McGraw-Hill International Edition, New York.

Banks J. (1998) Handbook of Simulation, John Wiley & Sons, Atlanta.

Banks J. (2001) Discrete-Event System Simulation (3ª ed.), Prentice-Hall, New Jersey.

Chung C.A. (2004) Simulation Modeling Handbook. A Practical Approach, CRC Press, Boca Raton.

Pidd M. (1994) Computer Simulation in Management Science, John Wiley & Sons, Singapore.

Teaching method

In lectures the expositive method is adopted to present concepts, methods and models. Oral questions are frequently made for prerequisite control, knowledge assessment and stimulate students’ participation.

In laboratory sessions the experimental method is adopted. Active methods are used. Students are challenged with multifaceted problems which should be solved in team. Also, case studies are analyzed and discussed in class. 

Evaluation method

The course grading is based on closed-book tests (T1 and T2) and projects (1 individual, Trb-I, and the other in a team, Trb-Gr), with a weighting of 60 and 40% in the final grade, respectively.

Final grade =  0,3 T1 + 0,3 T2 + 0,1 Trb-I + 0,3 Trb-Gr

T1: 18 oct; T2: 6 dec; Trb-I: 17/19 oct

To be exempted from the final exam, the student must assure a mark equal or above 9,5 in the average of closed-book tests.

The student is excluded from final exam if not present in at least 9 lectures and 9 laboratory sessions.