Abstract
Coloring a k-colorable graph using k colors (k≥3) is a notoriously hard problem. Considering average case analysis allows for better results. In this work we consider the uniform distribution over k-colorable graphs with n vertices and exactly cn edges, c greater than some sufficiently large constant. We rigorously show that all proper k-colorings of most such graphs lie in a single "cluster", and agree on all but a small, though constant, portion of the vertices. We also describe a polynomial time algorithm that whp finds a proper k-coloring of such a random k-colorable graph, thus asserting that most such graphs are easy to color. This should be contrasted with the setting of very sparse random graphs (which are k-colorable whp), where experimental results show some regime of edge density to be difficult for many coloring heuristics.
Original language | English |
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Pages (from-to) | 523-565 |
Number of pages | 43 |
Journal | Theory of Computing Systems |
Volume | 46 |
Issue number | 3 |
DOIs | |
State | Published - 1 Apr 2010 |
Externally published | Yes |
Keywords
- Average case analysis
- Random graphs
- Spectral analysis
- k-colorability
ASJC Scopus subject areas
- Theoretical Computer Science
- Computational Theory and Mathematics