Syllabus 2018-19

The syllabus is the following:

  1.  Operations Research Models
  2.  Graphical solution of MP problem in two variables
  3.  Convex and concave optimization
  4.  Unconstrained optimization: first and second order optimality conditions. The gradient method
  5.  Optimality conditions for inimization over a convex set. The conditional gradient method
  6. Equality constraied optimality conditions (Lagrange condition for linear constraints)
  7. Inequality Constrained optimization: optimality conditions  in the case of linear constraints: the Karush-Kuhn-Tucker conditions (Alternative theorems: Farkas Lemma)


  1. Linear Programming Theory: vertex and main LP theorem
  2. Duality theory for LP: economic use of shadow prices
  3. Integer Linear Programming: connection LP and ILP (unimodularity); Branch and Bound algorithm
  4. Multiobjective optimization
For more details see the Lectures page.