Some spin glass ideas applied to the clique problem
Statistical Mechanics
2015-06-25 v1 Disordered Systems and Neural Networks
Abstract
In this paper we introduce a new algorithm to study some NP-complete problems. This algorithm is a Markov Chain Monte Carlo (MCMC) inspired by the cavity method developed in the study of spin glass. We will focus on the maximum clique problem and we will compare this new algorithm with several standard algorithms on some DIMACS benchmark graphs and on random graphs. The performances of the new algorithm are quite surprising. Our effort in this paper is to be clear as well to those readers who are not in the field.
Cite
@article{arxiv.cond-mat/0605336,
title = {Some spin glass ideas applied to the clique problem},
author = {Antonio Iovanella and Benedetto Scoppola and Elisabetta Scoppola},
journal= {arXiv preprint arXiv:cond-mat/0605336},
year = {2015}
}
Comments
21 pages, latex file