Discrete mathematics - Graph theory and algorithms

linma1691  2018-2019  Louvain-la-Neuve

Discrete mathematics - Graph theory and algorithms
5 credits
30.0 h + 22.5 h
Blondel Vincent; Delvenne Jean-Charles; Jungers Raphaël (compensates Blondel Vincent);
This courses assumes that the elementary notions of discrete mathematics are acquired such as taught in LEPL1108.

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
Introduction to the language and theory of graphs : questions of characterization, isomorphism, existence and enumeration. Properties of directed and undirected graphs such as connectivity, planarity, k-colorability and the property of being Eulerian, perfect, etc. Modelling of practical problems : data structures and algorithms for the exploration of graphs. Basic graph algorithms and an analysis of their complexity.

At the end of this learning unit, the student is able to :


AA1 : 1,2,3

More precisely, by the end of the course the student will be able to :

  • model various problems in the language of graph theory
  • identify if a graph-theoretic problem has a known efficent algorithmic solution or not
  • propose and apply an algorithm to solve sucha a problem, at least for some classes of graphs
  • prove in a clear and rigorous fashion elementary properties related to the concepts covered in the course

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Structure and characterization of graphs - basic concepts - degree, connected components, path, cycle, cut, minor, etc. Classes of graphs and their recognition - perfect, series parallel, planar graphs, acyclic digraphs, etc. Exploration of graphs and tests of their properties - k-connected, eulerian, etc. Flows - theorems of Menger and Hall, maximum flow and minimum cost flow algorithms and their complexity. Problems :finding optimal matchings and stable sets, the travelling salesman problem, cut, graph partitioning and graph colouring problems
Teaching methods
The course is organized in lessons and supervised exercise sessions.
Evaluation methods
The students are evaluated individually through a written exam based on the specific objectives described above.
Ouvrage de base :
Syllabus sur moodle
Aussi :
  • Algorithmic Graph Theory, Alan Gibbons, Cambridge University Press 1985
  • Introduction to Graph Theory, Douglas West, Prentice Hall 1996.
  • Combinatorial Optimization, W.R. Cook et al., Wiley 1998.
  • Network Flows, Ahuja et al., Prentice Hall 1993.
Faculty or entity

Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Master [120] in Computer Science and Engineering

Master [120] in Electrical Engineering

Master [120] in Statistic: General

Master [120] in Computer Science

Bachelor in Engineering

Minor in Engineering Sciences: Applied Mathematics

Additionnal module in Mathematics