Random Constraint Satisfaction Problems
Discrete Mathematics
2009-11-13 v1 Computational Complexity
Data Structures and Algorithms
Abstract
Random instances of constraint satisfaction problems such as k-SAT provide challenging benchmarks. If there are m constraints over n variables there is typically a large range of densities r=m/n where solutions are known to exist with probability close to one due to non-constructive arguments. However, no algorithms are known to find solutions efficiently with a non-vanishing probability at even much lower densities. This fact appears to be related to a phase transition in the set of all solutions. The goal of this extended abstract is to provide a perspective on this phenomenon, and on the computational challenge that it poses.
Cite
@article{arxiv.0911.2322,
title = {Random Constraint Satisfaction Problems},
author = {Amin Coja-Oghlan},
journal= {arXiv preprint arXiv:0911.2322},
year = {2009}
}