Locked constraint satisfaction problems
Statistical Mechanics
2008-09-05 v2 Disordered Systems and Neural Networks
Computational Complexity
Abstract
We introduce and study the random "locked" constraint satisfaction problems. When increasing the density of constraints, they display a broad "clustered" phase in which the space of solutions is divided into many isolated points. While the phase diagram can be found easily, these problems, in their clustered phase, are extremely hard from the algorithmic point of view: the best known algorithms all fail to find solutions. We thus propose new benchmarks of really hard optimization problems and provide insight into the origin of their typical hardness.
Cite
@article{arxiv.0803.2955,
title = {Locked constraint satisfaction problems},
author = {Lenka Zdeborová and Marc Mézard},
journal= {arXiv preprint arXiv:0803.2955},
year = {2008}
}
Comments
4 pages, 2 figures