Introduction to Operational Research
Introduction to the scientific area of Operations Research, both in its components of modelling and optimization.
These two components will be approached under different Operations Research thematics, namely Inventory Control, Project Management, Decision Theory, Markov Chains and Simulation.
Since this is an introductory course, some of the subjects will be (or could be, as a student option) detailed in further courses of the curricular plan.
Nelson Fernando Chibeles Pereira Martins
Weekly - 5
Total - 90
1. "Elementos de apoio às aulas de Introdução à Investigação Operacional", "Enunciados de Exercícios de Introdução à Investigação Operacional", Ruy A. Costa
2. Investigação Operacional, Valadares Tavares et al, McGraw Hill
3 Investigação Operacional-Exercícios e Aplicações, Mourão et al, Verlag Dashofer
4. Introduction to Operations Research, Hillier e Lieberman, McGraw Hill
5. Operations Research - An Introduction, Taha, Prentice Hall
6. Operations Research- Applications and Algorithms, Winston, Brooks/Cole
On regular years, classes would take place in a computer lab. For this semester classes will be held , allowing students to acquire and immediately apply knowleon Zoom platform. The classes will be theoretical-practical, using spreadsheets and aditional software when required.
Theoretical notes and a set of exercises are provided to students.
Any questions or doubts will be addressed during the classes, during the weekly sessions specially programmed to attend students or in individual sessions previously scheduled between professor and students.
Students are regularly evaluated, during semester.
The Evaluation Method is fully described on the Course moodle area.
ALL STUDENTS MUST ATTEND TO A MINIMUM NUMBER OF LESSONS BEFORE BEING ACCEPTED TO EVALUATION.
Contact the Responsible Professor for aditional information: email@example.com
1 - Project Management (Critical Path Method; Gantt Diagram; Reducing the duration of a project; PERT technique).
2 - Inventory Control (basic deterministic models; extensions of the basic deterministic models).
3 - Decision Making (Decision under uncertainty and risk; Utility. Introduction to multicriteria decision making; Sequential decisions).
4- Markov Chains in Discrete Time (Definition; Transition probabilities; Decomposition of an homogeneous chain; Limit theorems).
5 - Simulation (Generating of pseudo-random numbers; Applications).