Base Knowledge
Not applicable.
Teaching Methodologies
Lectures and discussion and resolution of problems and case studies.
Learning Results
Building mathematical models (linear, integer and binary) to be used in obtaining the optimal solution of a problem. Solving linear programming problems using the simplex algorithm and computational tools (MS Excel Solver). Sensitivity analysis of a linear programming problem solution, dealing with the uncertainty in the model. Binary and integer programming formulation and solution using computational tools. Writing and solving transport, shortest path and maximum flow problems. Using decision theory and criteria in the selection of options in the presence of uncertainty. Identification different stock management models and optimal policies.
Program
Formulation and solution of linear, integer and binary programming problems. Sensitivity analysis. Allocation problems. Network problems: transportation, maximum flow, shortest path. Decision theory: criteria and decision tree. Stock management: deterministic, stochastic and multilevel models.
Curricular Unit Teachers
Grading Methods
- - Teste escrito - 30.0%
- - Trabalho de grupo (caso de estudo) - 35.0%
- - Trabalho individual - 35.0%
- - Prova escrita - 100.0%
Internship(s)
NAO
Bibliography
Hillier F.S., Lieberman G.J., 2015. Introduction to Operations Research, 10th ed., McGraw Hill Education.
Plà-Aragonés, L.M. (ed.), 2015. Handbook of Operations Research in Agriculture and the Agri-Food Industry, International Series in Operations Research and Management Science, vol. 224, Springer.
Carter, M.W., Price, C.C., Rabadi, G. (2019). Operations Research: A Pratical Introduction, 2nd ed. CRC Press.