Decision Support Models

There are no basic knowledge prerequisites other than those required for admission to this Master course.

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 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.

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.

Students will be assessed by an assignment project carried out during the course and a final written test. The assignment is optional, while the written test is compulsory. The final mark will be equal to 50% of the mark for the assignment, plus 50% of the mark for the written test. The work grade will only be considered if the student obtains a minimum mark of 7.5 in the written test (on a scale of 0 to 20). If the student chooses not to do the assignment, their final grade will be determined entirely by the written test.
The following assessment methodologies (MA) will be used:
MA1 - Final exam.
MA 2 - Practical work on one of the topics covered in the P5 syllabus (optional).

In the event of a well-founded suspicion of fraud detected during the marking of the examination, the student will be called to sit an oral examination to verify the knowledge and skills demonstrated. This verification is carried out by an examination board comprising the lecturer responsible for the course unit and two further lecturers from the same subject area. Should the student fail to demonstrate that they possess the knowledge and skills demonstrated in the written examination, their examination will be invalidated.

NAO