Average-case complexity of a branch-and-bound algorithm for max independent set under the G(n,p) random model

Nicolas Bourgeois (1) , Rémi Catellier (2) , T Denat (3) , Vangelis Th Paschos (3)

1 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne)
2 IRMAR - Institut de Recherche Mathématique de Rennes
3 LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision

We study average-case complexity of branch-and-bound for max independent set in random graphs under the G(n, p) distribution. In this model every pair (u, v) of vertices belongs to E with probability p independently on the existence of any other edge. We make a precise case analysis, providing phase transitions between subexponential and exponential complexities depending on the probability p of the random model.

Mots clés: Complexity Theory; Graphs

Domaines: Recherche opérationnelle [math.OC]

Nicolas Bourgeois, Rémi Catellier, T Denat, Vangelis Th Paschos. Average-case complexity of a branch-and-bound algorithm for max independent set under the G(n,p) random model. 2017. ⟨hal-01518581⟩