Decision Support Techniques

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

The teaching activity follows on a presential regime, with the exposition of concepts, techniques and methods.

Objectives:
Today’s economic systems are strongly influenced by conflicting and usually contradictory interests and are characterised by multiple factors of a wider and almost always complex system. It is in this context that the manager makes its moves, being regularly asked to take decisions.

Mathematical modelling techniques directed to some optimization and decision problems are introduced, including project planning, project selection, financial management, production management.

The course unit will also address the decision theory, focusing on the fundamentals of Bayesian Analysis, in order to implement decision criteria and models. The integration of active competitors is subsequently conducted through an approach modelled on Game Theory.

Competences:
The student is expected to show ability to model, in the context of linear and integer linear programming, some decision problems. The student must also know techniques and computer support tools to solve this type of mathematical models.

The fundamental knowledge of Bayesian Analysis and its application in the context of decision models, with and without active competitors, are also required in the student’s competences.

1 – Linear and integer linear programming models

   1.1 – Mathematical formulation of problems

   1.2 – Applications of mathematical modelling to Business Management

   1.3 – Economic analysis of the models

2 – Solving techniques for continuous linear and integer linear programming

   2.1 – Description of the most used methcontiunous and integer linear programming

   2.2 – Softwares for solving larger sized problems

3 – Economic interpretation of the solutions

   3.1 – Sensitivity analysis

   3.2 – Parametric analysis

4 – Applications of continuous and integer linear programming to the decision analysis process

   4.1 – Investments 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

5 – Decision analysis

   5.1 – Decision making process with and without experimentation

   5.2 – Decision trees

   5.3 – Sensitivity analysis

   5.4 – Utility theory

   5.5 – Decision Making in face of an active “competitor” – Game Theory

NAO

Essential Bibliography

–  Teaching materials produced by the teacher.

Supplementary Bibliography

– F.S. Hillier e G.J. Lieberman, Introdução à Pesquisa Operativa, McGraw Hill, 2006.

– R.L. Rardin, Optimization in Operations Research, Prentice Hall, New Jersey, 1998.

– W. J.  Stevensen, Operations Management, McGraw Hill, 8 th Ed, 2005.

– L.V. Tavares, R.C. Oliveira, I.H. Themido e F.N. Correia, Investigação Operacional, McGraw Hill, 1st Ed., 1996.