Heuristic Algorithms for Combinatorial Optimization Problems
A.Y. 2026/2027
Course offered to students on the PhD programme in
Visit the PhD website for the course schedule and other information
Lead instructor: Roberto Cordone
"Combinatorial Optimization is a huge domain of study, focused on optimization problems with a finite set of solutions.
It has important practical applications to manifold fields, including artificial intelligence, machine learning, routing, scheduling, location, network analysis and design.
As many Combinatorial Optimization problems are NP-hard, heuristics are a natural solution approach.
The teaching surveys the heuristics based on solution manipulations, classifying them into three families:
constructive/destructive heuristics, exchange heuristics and recombination heuristics.
It introduces the fundamental scheme of each family and discusses the properties that determine the efficacy of an algorithm (solution quality) and its efficiency (computational time and space), depending on the problem to which it is applied. It also discusses the introduction of mechanisms based on randomisation and memory, that turn the classical heuristics into the so called metaheuristics.
A part of the teaching is dedicated to the methods to assess the performance of optimisation algorithms."
It has important practical applications to manifold fields, including artificial intelligence, machine learning, routing, scheduling, location, network analysis and design.
As many Combinatorial Optimization problems are NP-hard, heuristics are a natural solution approach.
The teaching surveys the heuristics based on solution manipulations, classifying them into three families:
constructive/destructive heuristics, exchange heuristics and recombination heuristics.
It introduces the fundamental scheme of each family and discusses the properties that determine the efficacy of an algorithm (solution quality) and its efficiency (computational time and space), depending on the problem to which it is applied. It also discusses the introduction of mechanisms based on randomisation and memory, that turn the classical heuristics into the so called metaheuristics.
A part of the teaching is dedicated to the methods to assess the performance of optimisation algorithms."
Knowledge of fundamental algorithms and data structures
Assessment methods
Giudizio di approvazione
Assessment result
superato/non superato
How to enrol
Deadlines
The course enrolment deadline is usually the 27th day of the month prior to the start date.
How to enrol
- Access enrolment on PhD courses online service using your University login details
- Select the desired programme and click on Registration (Iscrizione) and then on Register (Iscriviti)
Ignore the option "Exam session date” that appears during the enrolment procedure.
Contacts
For help please contact [email protected]
Professor(s)
Reception:
By appointment
DI - Via Celoria 18, Milan