Decision Support Methods / Métodos de Apoio à Decisão
- to get acquainted with the operations research techniques for modelling and solving decision problems;
- to develop skills for understanding the computational complexity of concrete problems, and choosing algorithms, programming languages and libraries/APIs for solving them;
- to prime on analysing and discussing the results obtained.
Competences developped in this course
Mastering the main techniques in optimization and simulation.
- Introduction to operations research.
- Mathematical programming: formulation, model classification.
- Linear programming: the simplex algorithm, duality, examples of application.
- Networks: basic graph theory, typical problems.
- Project planning.
- Introduction to integer programming. Branch-and-bound and cutting-plane alrorithms.
- Constraint programming.
- Short introduction to non-linear programming.
- Markov chains.
- Dynamic programming.
- Page of this course in SIGARRA information system
- Used software:
- Solving Constraint Integer Programs SCIP
- GNU Linear Programming Kit GLPK
- Modelling language AMPL
- F. Hillier, G. Lieberman. Introduction to Operations Research. McGraw-Hill. (Main reference)
- W.L. Winston. Operations research.
- K. Marriott, P. Stuckey. Programming with Constraints, MIT Press.
- G. Sierksma. Linear and integer optimization.