Constraint optimization and landscapes
Quantum Physics
2008-09-25 v1 Statistical Mechanics
Computational Complexity
Adaptation and Self-Organizing Systems
Abstract
We describe an effective landscape introduced in [1] for the analysis of Constraint Satisfaction problems, such as Sphere Packing, K-SAT and Graph Coloring. This geometric construction reexpresses these problems in the more familiar terms of optimization in rugged energy landscapes. In particular, it allows one to understand the puzzling fact that unsophisticated programs are successful well beyond what was considered to be the `hard' transition, and suggests an algorithm defining a new, higher, easy-hard frontier.
Cite
@article{arxiv.0709.1023,
title = {Constraint optimization and landscapes},
author = {Florent Krzakala and Jorge Kurchan},
journal= {arXiv preprint arXiv:0709.1023},
year = {2008}
}
Comments
Contribution to STATPHYS23