Basic definitions and results in graph theory and network flows.
Knowledge and understanding:
– know both exact and heuristic techniques for classes of optimization problems which are relevant in the managment of real systems;
– be able to formally express a solution procedure using a programming language or a pseudocode;
Applying knowledge and understanding:
– be able to recognize the main aspects which are relevant in modeling a real optimization problem (variables, constraints, objective function);
– be able to evaluate the complexity of a problem and the effectiveness of an algorithm proposed for its solution;
Autonomy of judgment:
– be able to identify possible types of models and solution procedures for an optimization problem;
– be able to help in analyzing and correctly formulating a model for an optimization problem of the production / industrial world;
– know the language of graph theory and mathematical optimization;
– be able to present the content of a scientific O.R. article;
– be able of self-study from the recommanded bibliography;
– know how to formulate appropriate models for the problems discussed in class and for other defined autonomously.