Elementary matrix algebra and calculus. Matrix operations, inverse matrix, convexity, derivatives, gradient. The student must have passed Linear Algebra and Calculus I.
Learn the fundamental methods and tools to formulate and solve constrained, unconstrained and graph optimization problems.
Basics of mathematical programming, linear programming.
Optimality conditions in uncontrained optimization. Optimality conditions in contrained optimization: KKT conditions. Linear Programming, duality. Polyhedra. Basic feasible solutions and geometry of LP. Simplex method. Sensitivity to parameter variations. Formulation of decision problem as LP.
-- M. Fischetti, Lezioni di Ricerca Operativa, Libreria Progetto, Padova.
-- A. Agnetis, downloadable classnotes
Lectures and exercises.
Written and oral tests.