Teaching Methodologies
The classes in this course are theoretical and practical in nature.
At first, the classes are more expository, aimed at establishing the theoretical basis of the subjects covered, followed by the practical
component, with the application to complex decision problems in the field of Management, aimed at a prescriptive analysis of these
problems. The mathematical resolution of these problems will use specific software, seeking to answer large-scale problems within the
scope of the themes proposed in the P4 syllabus.
The following teaching-learning methodologies will be used:
TM1 – Expository: presentation of concepts, techniques and methods, with a strong focus on practical applications.
TM2 – Participative: in-class discussion of cases within the scope of the themes in the P4 syllabus, developing skills in prescriptive analysis.
TM2 – Active: use of software to support the resolution of larger problems, allowing laboratory spaces that encourage the autonomous use
of these computer applications.
TM3 – Group work: an assignment will be proposed (in groups) to apply the methodologies presented, in which the student applies the
knowledge acquired to a practical case within the scope of the topics proposed in the P4 syllabus.
Learning Results
Learning objectives (LO):
LO1. Introduction of mathematical modelling techniques aimed at complex decision problems in Planning and Management, using linear
and integer linear programming.
LO2. Solving applied cases, focusing on: project selection, production management, financial management, project planning and work
schedules and shifts, among others.
LO3. Using computer optimization tools to solve the proposed mathematical models.
Competences to be developed (C):
C1. Ability to model complex management decision problems using linear and integer linear programming.
C2. Ability to efficiently use mathematical optimization tools to answer the proposed problems.
C3. Ability to perform prescriptive analysis on those problems, explore and interpret the results generated and apply them to real cases.
Program
P1 – Linear and integer linear programming models
1.1 – Mathematical formulation of problems
1.2 – Application of mathematical modelling to management decision problems
1.3 – Economic analysis of the models
P2 – Techniques for solving linear and integer linear programmes
2.1 – Description of the main methods in continuous and integer linear programming
2.2 – Software for solving larger problems
P3 – Economic interpretation of the solutions
3.1 – Sensitivity analysis
3.2 – Parametric analysis
P4 – Applications of linear and integer linear programming to the decision-making process
4.1 – Investment planning and project selection with cash flows
4.2 – Production management
4.3 – Financial management
4.4 – Project planning
4.5 – Shift scheduling and rostering.
Internship(s)
NAO
Bibliography
Fundamental:
– Martins, P., Elementos de apoio disponibilizados na plataforma NONIO, Edição do Autor.
Complementar:
– Hillier, F. S., & Lieberman, G. J. (2021). Introduction to Operations Research, Mc Graw-Hill. ISBN: 978-0-071-13989-2
– Rardin, R.L. (2017), Optimization in Operations Research (2nd ed.), Pearson Higher Education, Hoboken. ISBN: 978-0-13-438455-9