A study of evaluation functions for the graph K-coloring problem.

International audienceAbstract. The evaluation or fitness function is a key component of any heuristic search algorithm. This paper introduces a new evaluation function for the well-known graph K-coloring problem. This function takes into account not only the number of conflicting vertices, but also inherent information related to the structure of the graph. To assess the effectiveness of this new evaluation function, we carry out a number of experiments using a set of DIMACS benchmark graphs. Based on statistic data obtained with a parameter free steepest descent, we show an improvement of the new evaluation function over the classical one

Intensification/Diversification-Driven ILS for a Graph Coloring Problem

International audienceThis paper presents an extension of the ILS algorithm, called ID-ILS, by introducing new local search devices that enforce an efficient tradeoff of intensification and diversification. Experiments performed on the DIMACS benchmarks show that our method is competitive with the best coloring algorithms