Abstract: The graph coloring problem is often investigated in the literature. Many insights about many neighboring solutions with the same fitness value are raised but as far as we know, no deep analysis of this neutrality has ever been conducted in the literature. In this paper, we quantify

Ant Colony Optimization (ACO) is a well-known metaheuristic in which a colony of artificial ants cooperates in exploring good solutions to a combinatorial optimization problem. In this paper, an ACO algorithm is presented for the graph coloring problem. This ACO algorithm conforms to Max-Min Ant

Important notice: This is a draft of my official PhD thesis (in French). The jury did not read this document but the official version should be available on the same webpage. The French version has been initially written by translating this draft; while I do not claim it is a strict verbatim translation, most of the information can be found in the French version (e.g. the table of contents has the same structure).

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In this work, the Graph Coloring Problem and its general-izations- the Bandwidth Coloring Problem, the Multicol-oring Problem and the Bandwidth Multicoloring Problem- are studied. A Squeaky Wheel Optimization with Tabu Search heuristic is developed and experiments using bench-mark geometric test

This paper presents a generalization of the graph coloring problem. We study its properties and generalize some well-known bounds and de nitions.We propose a generalization of perfect graphs and analize the complexity of the problem. An heuristic is developed toseek "good" solutions

Abstract. We present an automated algorithm selection method based on machine learning for the graph coloring problem (GCP). For this purpose, we identify 78 features for this problem and evaluate the performance of six state-of-the-art (meta)heuristics for the GCP. We use the obtained data

Graph coloring and its generalizations are useful tools in modeling a wide variety of scheduling and assignment problems. In this paper we review several variants of graph coloring, such as precoloring extension, list coloring, multicoloring, minimum sum coloring, and discuss their applications

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