Providing the students with methodological and application competences in the area of operations planning and management in the context of engineering problems, in order to enable them to identify types of problems, develop mathematical models that include the essential characteristics of those problems, and apply algorithms to generate solutions for the problems, and to perform a critical analysis of the solutions obtained.
1. Introduction to linear programming (LP). The simplex method.
2. Project planning and management. The PERT method with most probable, optimistic and pessimistic estimates for the activity duration. The CPM method. Project scheduling. Project analysis in the resource space. Heuristic for resource leveling.
3. Inventory theory models. Deterministic models. Stochastic models (order level and cyclic revision policies). Global and partial optimization models.
4. Forecasting. Time series. Linear regression. Non-linear and multiple regression.
5. Decision analysis. Decision making without and with experimentation. Decision trees. Utility functions.
6. Queueing theory. Birth and death processes. Little’s formula. M/M/1 and M/M/S models. Queues with limited length. Queues with finite population. Models involving other distributions.
Linear Algebra, Probabilities and Statistics, Calculus
Generic skills to reach
. Competence in analysis and synthesis; . Competence in organization and planning; . Competence to solve problems; . Capacity of decision; . Critical thinking; . Competence in understanding the language of other specialists; . Adaptability to new situations; . Creativity; . Competence in applying theoretical knowledge in practice; . Planning and managing; (by decreasing order of importance)
Teaching hours per semester
total of teaching hours
assessment implementation in 20132014 Assessment Mini Tests: 25.0% Exam: 75.0%
Bibliography of reference
- Hillier, F. S., G. J. Lieberman. Introduction to Operations Research, McGraw-Hill, 2005 (8th ed.).
- Tavares, L. V., R. C. Oliveira, I. H. Themido, F. N. Correia. “Investigação Operacional”, McGraw-Hill Portugal, 1996.
- Bronson, R., G. Naadimuthu. Investigação Operacional, Colecção Schaum (2ª. Ed.), McGraw-Hill Portugal, 2001.
- Clímaco, J., C. H.Antunes, M. J. Alves. Programação Linear Multiobjectivo, Imprensa da Universidade de Coimbra, 2003.
- Chang, Y.L. WinQSB, Decision Support Software for M/OM (ver 2.0), Wiley, 2003.
- Antunes, C. H., L. V. Tavares (Coord.). Casos de Aplicação da Investigação Operacional, McGraw-Hill, 2000.
Theoretical and methodological concepts are presented in tutorial lectures, being motivated by real-world problems and illustrated with application examples.
Software (commercial and public domain) packages are used to obtain solutions to the mathematical models, thus freeing the students for the more creative tasks of problem formulation, model building and critical analysis of results.