Graphs and algorithms
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Fundamental properties of neighbourhood substitution in constraint satisfaction problems
Artificial Intelligence
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
A lower bound on the chromatic number of mycielski graphs
Discrete Mathematics
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
New Results on the Queens_n2 Graph Coloring Problem
Journal of Heuristics
Coloring graphs by iterated local search traversing feasible and infeasible solutions
Discrete Applied Mathematics
Exact and approximate link scheduling algorithms under the physical interference model
Proceedings of the fifth international workshop on Foundations of mobile computing
Using hajós' construction to generate hard graph 3-colorability instances
AISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Symbolic Computation
A CSP search algorithm with reduced branching factor
CSCLP'05 Proceedings of the 2005 Joint ERCIM/CoLogNET international conference on Constraint Solving and Constraint Logic Programming
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In this paper we propose a method for integrating constraint propagation algorithms into an optimization procedure for vertex coloring with the goal of finding improved lower bounds. The key point we address is how to get instances of Constraint Satisfaction Problems (CSPs) from a graph coloring problem in order to give rise to new lower bounds outperforming the maximum clique bound. More precisely, the algorithms presented have the common goal of finding CSPs in the graph for which infeasibility can be proven. This is achieved by means of constraint propagation techniques which allow the algorithms to eliminate inconsistencies in the CSPs by updating domains dynamically and rendering such infeasibilities explicit. At the end of this process we use the largest CSP for which it has not been possible to prove infeasibility as an input for an algorithm which enlarges such CSP to get a feasible coloring. We experimented with a set of middle-high density graphs with quite a large difference between the maximum clique and the chromatic number.