Operations Research

Objectives

Introduction to the scientific area of Operational Research, both in its components of modelling and optimization.

These two components will be approached under different Operational Research thematics, namely Project Management, Inventory Control, Networks Optimization, 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.

General characterization

Code

12917

Credits

9.0

Responsible teacher

Maria do Carmo Proença Caseiro Brás

Hours

Weekly - 4

Total - 66

Teaching language

Português

Prerequisites

Available soon

Bibliography

1. "Elementos de apoio às aulas de Introdução à Investigação Operacional", "Enunciados de Exercícios de Introdução à Investigação Operacional", Ruy A. Costa (2007)

2. Investigação Operacional, Valadares Tavares et al, McGraw Hill (1997)

3. Wayne L. Winston, Operations Research: Applications and Algorithms, Brooks/Cole; 4th edition, 2004.

4. Introduction to Operations Research, Hillier e Lieberman, McGraw Hill (1995)

5. Operations Research - An Introduction, Taha, Prentice Hall (2011)

Teaching method

The classes will be theoretical-practical, allowing students to acquire and immediately apply knowledge. Classes will use 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 on individual sessions previously scheduled between professor and students.

Students are regularly evaluated, during semester.

Evaluation method

Registration for In-Person Exams (Tests and Exams)

To optimize the resources of NOVA FCT (facilities, teaching staff, and non-teaching staff), only students properly registered through the course''s CLIP page may present themselves for any in-person exam. They must also bring a blank exam notebook, writing materials, scientific basic calculator, and an official identification document with a recent photo.


Continuous Assessment

The continuous assessment of the course is conducted through Theoretical-Practical Assessment, which includes two in-person tests, each lasting 1.5 hours.

Let T1 and T2 be the grades for each of the two tests, expressed on a scale of 0 to 10 points, rounded to the nearest tenth. A student will have a final grade of T1 + T2, rounded to the nearest whole number.

The student will pass the course if this final grade is greater than or equal to 10 points. Otherwise, the student will have failed the course by continuous assessment.

Resit Period

Students who fail by continuous assessment may take the resit exam, which will last 3 hours.

The final grade for the student in the resit period will be obtained exclusively from the exam grade. The student will pass the course if this final grade is greater than or equal to 10 points. Otherwise, the student will have failed the course.

Grade Review

All students with a final grade higher than 17 points (by continuous assessment or in the resit period) may, if they wish, take a grade review exam. Not taking this exam implies a final grade of 17 points for the course.

Subject matter

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 - Networks Optimization. (Introduction to Graph Theory. Shortest Path Problem. Dijsktra Algorithm. Floyd–Warshall Algorithm. Minimal Spanning Tree. Prim Algorithm. Kruskal Algorithm. Eulerian Graphs. Chinese Postman Problem. Hamiltonian Graphs. Traveling Salesman Problem.

4 - Decision Making (Decision under uncertainty and risk; Utility. Introduction to multicriteria decision making; Sequential decisions).   

5- Markov Chains in Discrete Time (Definition; Transition probabilities; Decomposition of an homogeneous chain; Limit theorems).

6 - Simulation (Generating of pseudo-random numbers; Applications).