Laboratoire de Génie Informatique et d’Automatique de l’Artois


Belief functions: from theory to practice

Keywords: Decision support systems, Imperfect data, Belief functions, Information Fusion.

In this document, the conception of decision support systems in an imperfect context is approached. The goal of these systems is to help the expert to make a decision in the case of complex systems. A complex system is a system for which the decision is based on a large number of information. Moreover, these information can be imperfect (imprecise, uncertain, incomplete, etc.).

To realize decision support systems, three steps are needed:

  1. the data acquisition,
  2.  the modelling the information,
  3. the knowledge extraction (or make the sense) to provide help to the expert for making a decision.

In this habilitation thesis, two last steps of this process are explained. To deal with the imperfect information, we use the belief function theory considered as the unifying formalism in the uncertainty theories. This theory allows us to easily represent the knowledge. Furthermore, the conception of two decision support systems is introduced in this manuscript. The first application concerns the selection of supplier in the framework of supply chain management, whereas second one deals with the decision support for forensic investigation.

Involved research axes:

No partner is associated with this element.


Defense took place the 11/12/2012 am31 10:00 Prestige room - FSA - Béthune


  • Rapporteur Michèle ROMBAUT Université J. Fourier
  • Rapporteur Laurent FOULLOY PolyTech' Savoie
  • Rapporteur Arnaud MARTIN Université Rennes 1
  • Examinateur Olivier COLOT Université Lille 1
  • Examinateur François DELMOTTE Université d'Artois
  • Examinateur Thierry DENOEUX UTC
  • Examinateur Nour eddin EL FAOUZI IFSTTAR
  • Advisor Daniel JOLLY Université d'Artois