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L. Vice-président-du-conseil-scientique-chargé-de-la-recherche-de-l-'université and P. Les, une représentation graphique compacte et expressive des préférences d'un décideur en Décision Multiattribut, c'est-à-dire dans des situations où les alternatives sur lesquelles portent les choix du décideur sont décrites à l'aide d'un ensemble d'attributs (de caractéristiques) L'exploitation de leur structure graphique permet de dénir des procédures ecaces d'élicitation de préférences (détermination des préférences à l'aide de questionnaires) ainsi que des algorithmes assez performants de prise de décision (calcul de l'alternative préférée du décideur ou des k meilleures alternatives) Le but de cette thèse est double. Tout d'abord elle vise à étendre les algorithmes de prise de décision dans des cas où les réseaux GAI sont denses, c'est-à-dire dans des situations où leur structure ne permet pas aux algorithmes de l'état de l'art de s'exécuter en un temps raisonnable . Pour cela, une nouvelle méthode de triangulation approchée a été développée, qui produit des réseaux GAI approchés sur lesquels des mécanismes d'inférence adaptés permettent d'obtenir les alternatives optimales des réseaux GAI d'origine. Ensuite, elle propose de nouvelles méthodes d'inférence en Décision multicritère

. Mots-clés, Aide à la décision, décision multiattribut, décision multicritère, modélisation des préférences, optimisation combinatoire, graphes