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The cluster analysis has several methods that aim to identify groups within a dataset. This paper presents new heuristics based on Iterated Local Search metaheuristic to solve the Automatic Clustering Problem. The Silhouette index combines both cohesion and separation concepts, and it is considered by proposed heuristics to evaluate the solutions. According the computational experiments, the effectiveness and efficiency of the ILS-DBSCAN are reflected in substantially lower runtimes and in the solutions' quality, which are competitive with best results reported in the literature. This way, the use of the ILS-DBSCAN is a new promising way to solve the problem.

UMA HEURÍSTICA BASEADA EM DENSIDADE PARA O PROBLEMA DE AGRUPAMENTO AUTOMÁTICO