– Knowledge and understanding: know the fundamental properties of the convex sets; know the theory, the main methodologies, the computational aspects and some classical applications of linear programming; know the theory, the main methodologies and the computational aspects of integer linear programming and the ILP models of some classical combinatorial problems; know the main concepts and problems of the graph theory and their complexity.
– Applying knowledge and understanding: be able to formulate an LP/ILP model for simple combinatorial/real-life problems; be able to apply duality arguments to solve pairs of primal-dual LP problems; be able to solve simple LP/ILP instances using the appropriate algorithms; be familiar with the technique of sensitivity analysis.
– Autonomy of judgment: be able to identify a suitable LP/ILP/graph model for simple combinatorial/real-life problems.
– Communication skills: be able to present the subjects of the course with rigor and completeness.
– Learning skills: be able to further deepen the course topics in relation to aspects not performed in class.
– Lecture notes