Jeudi 5 Novembre
Heure: 
10:30  11:30 
Lieu: 
Salle B107, bâtiment B, Université de Villetaneuse 
Résumé: 
An exact algorithm for robust influence maximization 
Description: 
Roberto Wolfler Calvo We propose a BranchandCut algorithm for the robust influence maximization problem. The influence maximization problem aims to identify, in a social network, a set of given cardinality comprising actors that are able to influence the maximum number of other actors. We assume that the social network is given in the form of a graph with node thresholds to indicate the resistance of an actor to influence, and arc weights to represent the strength of the influence between two actors. In the robust version of the problem that we study, the node thresholds are affected by uncertainty and we optimize over a worstcase scenario within a given robustness budget. Numerical experiments show that we are able to solve to optimality instances of size comparable to other exact approaches in the literature for the nonrobust problem, but in addition to this we can also tackle the robust version with similar performance. 

