Introduction to Operations Research


In this course Engineering students are introduced to the first concepts of Operations Research. The course will introduce students to the following O.R. subjects: Linear Programming, Decision Theory, Queueing theory and Simulation.

General characterization





Responsible teacher

Ruy Araújo da Costa


Weekly - 4

Total - 56

Teaching language



Students are required to have basic knowledge of Linear Algebra and Probability Theory.


1. Introduction to Operations Research (1990 - 5ªEd.), Hillier, Lieberman - Mc Graw Hill
2. Operations Research - An Introduction(1992 - 5ª Ed.) Taha - Prentice Hall
3. "Elementos de apoio às aulas de IIO", "Enunciados de Exercícios de IIO", Ruy A. Costa 
4. Investigação Operacional (1996), Valadares Tavares et al - Mc Graw Hill   

Teaching method

In 2020/21, due to the SARS Covid-19 pandemic, all classes will be online and exclusivelly in Portuguese.

Any non-Portuguese student should contact the Professors if (s)he requires any assistance. 

Basic concepts will be introduced in lectures ("aulas teóricas") and problems will be solved in problem solving classes ("Aulas práticas").

Moodle e-learning platform will be used to carry out weekly learning activities.

Evaluation method

For full details please access the pdf file in Documentação de Apoio > Outros

For further information, you should contact Prof. Ruy Costa, .

Students should attend at least 2/3 of the practical lessons.There are 2 Tests during the semester and one Exam afterwards.

Subject matter

1 – Linear Programming:

Linear Programming Formulations;

Graphic Method;

Simplex Algorithm;

Sensitivity Analisys;

Linear Integer Programming: Branch and Bound Algorithm;

Trasportation Problem.

2 – Decision Theory:

Decisions under risk and under uncertainty;

Decision Trees.

3 – Queueing Theory:

Basic Structure of Queueing Systems;

Birth and Death Queueing Models;

Queueing Models with non-Exponencial distributions;

Queueing Models with Priorities;

Waiting Queues Networks.

4 – Simulation:

Pseudo-Random Numbers Generation Methods;

Aplications to Queueing Theory.