En raison de la crise du COVID-19, les informations ci-dessous sont susceptibles d’être modifiées,
notamment celles qui concernent le mode d’enseignement (en présentiel, en distanciel ou sous un format comodal ou hybride).
5 crédits
30.0 h + 15.0 h
Q1
Enseignants
Catanzaro Daniele; Meskens Nadine;
Langue
d'enseignement
d'enseignement
Anglais
Préalables
Le(s) prérequis de cette Unité d’enseignement (UE) sont précisés à la fin de cette fiche, en regard des programmes/formations qui proposent cette UE.
Contenu
This course is taught in English and aims to introduce to the foundations of integer programming and combinatorial optimization as well as the main computing techniques to tackle and solve a discrete optimization problem.
Table of Contents: Mathematical Preliminaries; Fundamental problems in linear algebra and number theory; Optimizing over diophantine inequalities with positivity constraints; Optimality, relaxations families and relationships among relaxations, and type of bounds; Efficiently solvable combinatorial optimization problems; Rudiments of computational complexity; General solution approach to optimization over integers; Introduction to polyhedral combinatorics; Branch-and-cut; Fundations of the Mosel programming language and applications.
Table of Contents: Mathematical Preliminaries; Fundamental problems in linear algebra and number theory; Optimizing over diophantine inequalities with positivity constraints; Optimality, relaxations families and relationships among relaxations, and type of bounds; Efficiently solvable combinatorial optimization problems; Rudiments of computational complexity; General solution approach to optimization over integers; Introduction to polyhedral combinatorics; Branch-and-cut; Fundations of the Mosel programming language and applications.
Méthodes d'enseignement
En raison de la crise du COVID-19, les informations de cette rubrique sont particulièrement susceptibles d’être modifiées.
Slided & Blackboard lectures.
Modes d'évaluation
des acquis des étudiants
des acquis des étudiants
En raison de la crise du COVID-19, les informations de cette rubrique sont particulièrement susceptibles d’être modifiées.
Students are assessed individually by means of an exam that consists of two parts:
1. An evaluation of the applied modeling skills, which is usually carried out during the last session of the exercizes and which focuses on the Mosel programming language as well as on the ability to model given toy problems. This part is carried out only once per year and the participation is mandatory for all of the students. A poor score on this part precludes the access to the second part (see point 2).
2. An evaluation of the theoretical skills of the students, carried out by means of a written exam during the standard examination sessions.
In the case of a red code due to the COVID crisis, an oral will replace the written exam mentioned in point 2.
Ressources
en ligne
en ligne
https://perso.uclouvain.be/daniele.catanzaro/Courses/Optimization.pdf
Bibliographie
The lectures will be integrated with some capita selecta from the following references: (1) S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press 2004. (2) L. A. Wolsey. Integer Programming. Wiley Interscience, 1988. (3) M. Conforti, G. Cornuejols, G. Zambelli. Integer Programming. Springer, 2014. (4) Bagirov, M. Karmitsa and M. M. Mäkelä. Introduction to non smooth optimization. Springer 2014. (5) F. F. Clarke. Optimization and nonsmooth analysis, Siam 1987.
Faculté ou entité
en charge
en charge
CLSM
Force majeure
Méthodes d'enseignement
Remote teaching
Modes d'évaluation
des acquis des étudiants
des acquis des étudiants
Remote orals
