Average-case complexity of a branch-and-bound algorithm for maximum independent set, under the $\mathcal{G}(n,p)$ random model
Computational Complexity
2015-05-20 v1
Abstract
We study average-case complexity of branch-and-bound for maximum independent set in random graphs under the distribution. In this model every pair of vertices belongs to with probability 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 of the random model.
Keywords
Cite
@article{arxiv.1505.04969,
title = {Average-case complexity of a branch-and-bound algorithm for maximum independent set, under the $\mathcal{G}(n,p)$ random model},
author = {N. Bourgeois and R. Catellier and T. Denat and V. Th. Paschos},
journal= {arXiv preprint arXiv:1505.04969},
year = {2015}
}