ࡱ> ,.+bjbjUU =??0 0 sssss  HhRN!sssss0Hs,H0 9:Abstract Recently, hybrid metaheuristics have become a trend in operations research. A successful example combines the Greedy Randomized Adaptive Search Procedures (GRASP) and data mining techniques, where frequent patterns found in high-quality solutions can lead to an efficient exploration of the search space, along with a significant reduction of computational time. In this work, a GRASP-based state-of-the-art heuristic for the Minimum Latency Problem (MLP) is improved by means of data mining techniques for two MLP variants. Computational experiments showed that the approaches with data mining were able to match or improve the solution quality for a large number of instances, together with a substantial reduction of running time. In addition, 88 new cost values of solutions are introduced into the literature. To support our results, tests of statistical significance, impact of using mined patterns, equal time comparisons and time-to-target plots are provided. Keywords: Minimum Latency Problem; Hybrid Metaheuristics; GRASP; Data Mining Resumo Recentemente, metaheursticas hbridas tm se tornado uma tendncia em pesquisa operacional. Um exemplo bem sucedido combina Greedy Randomized Adaptive Search Procedures (GRASP) e tcnicas de minerao de dados, onde padres frequentes encontrados em solues de alta qualidade podem levar a uma explorao eficiente do espao de busca, juntamente com uma reduo significativa de tempo computacional. Neste trabalho, uma heurstica estado-da-arte baseada em GRASP para o Problema da Mnima Latncia (PML) aperfeioada por meio de tcnicas de minerao de dados em duas variantes do PML. Experimentos computacionais mostraram que as abordagens com minerao de dados igualaram ou melhoraram a qualidade de soluo para um nmero expressivo de instncias, juntamente com uma reduo substancial de tempo de execuo. Alm disso, 88 novos valores de custos de solues de ambos problemas so introduzidos na literatura. Para avaliar os resultados reportados, testes de significncia estatstica, impacto de uso de padres minerados, comparaes de mesmo tempo e grficos time-to-target so apresentados. 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