Graph Optimization
A.Y. 2025/2026
Learning objectives
The objectives of the course are: 1) to learn some polynomial time algorithms for graph optimization problems and the theoretical foundations on which these algorithms are based; 2) to implement some of the algorithms presented (a part of the course takes place in a computer lab); 3) to understand when the search for polynomial algorithms, for a new combinatorial optimization problem, is probably destined to fail (by means of the computational complexity theory).
Expected learning outcomes
Ability to design and implement efficient algorithms to solve polynomial complexity optimization problems on graphs.
Lesson period: Second four month period
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second four month period
MAT/09 - OPERATIONS RESEARCH - University credits: 6
Lessons: 48 hours
Professor:
Righini Giovanni
Shifts:
Turno
Professor:
Righini GiovanniProfessor(s)