Arborescence des pages
ConfigureOutils de l'espace
Aller directement à la fin des métadonnées
Aller au début des métadonnées

GIMAS8AE

Advanced Discrete Optimization

 

ECTS Credits: 2

Duration: 21 hours

 

Semester: S8

Person(s) in charge:

Bernadetta ADDIS, Lecturer, bernadetta.addis@mines-nancy.univ-lorraine.fr

Keywords: Discrete optimisation

Prerequisites: course SG134: Discrete Optimization

Objective:

Advanced techniques in discrete optimisation

Program and contents

Objectives

 

First, we present different approaches to constructing exact and approximated methods for difficult optimisation problems. These approaches will be illustrated on different examples already modeled in the course SG 134. The approximation methods can be constructed with guaranteed performance in comparison with the optimal solution. The second part of this course will be dedicated to generic methods for combinatorial problems such as meta-heuristics, evolutionist algorithms (genetic algorithms) as well as constraint programming.  In last part, we present other analysis techniques when we are in the presence of problems with several criteria.

 

Content 

  •  Exact Methods such as branch and bound
  • Relaxation and approximation of optimisation problems
  • Meta-heuristics and genetic algorithms
  • Constraint programming
  • Multi-criteria analysis of optimisation problems.

 

Abilities: 

Levels

Description and operational verbs

Know 

 

Understand 

 

Apply 

 

Analyze 

 

Summarise

 

Assess

 

Evaluation:

  • Written test
  • Continuous Control
  • Oral report
  • Project
  • Written report
  • Aucune étiquette