97271 - Mathematical Programming

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Affordable and clean energy Industry, innovation and infrastructure Sustainable cities Responsible consumption and production

Academic Year 2021/2022

Learning outcomes

At the end of the course the student knows the main theoretical and algorithmic methods of mathematical programming for the solution of optimization problems and decision support; is able to analyse an optimization problem and develop the appropriate mathematical model for its resolution. The course includes the illustration of real world applications and laboratory experiences which shows how to implement an algorithm based on a mathematical programming model and how to use the main available solvers.

Course contents

Introduction to Mathematical Programming (Mathematical Optimization). Linear Programming and Integer Linear Programming models. Simplex Algorithm. Duality Theory, Dual Simplex Algorithm. Methods for integer problems: Branch & Bound, Branch & Cut, Column Generation. Use of commercial and public domain solvers.


Matteo Fischetti Introduction to Mathematical Optimization, Self Published in Amazon

Lecture notes and slides from the teacher

Teaching methods

Frontal lectures and exercise sessions

Assessment methods

Oral Exam with exercises and theoretical questions

Teaching tools

Lecture notes and slides from the teacher

Office hours

See the website of Daniele Vigo