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In this paper, we describe and show the results of a combination of two metaheuristics to solve an unrelated parallel machines scheduling problem in which the setup times depend not only on the machine and job sequence, but also on the amount of resource assigned. This problem has been proposed recently on the literature and since then a couple of metaheuristics have been used to address it. The one proposed here, called GTS, consists of two phases: initially, some solutions are generated by the GRASP metaheuristic; subsequently, the Tabu Search (TS) is applied in the best solution found by GRASP. The numerical experiments show that the GTS heuristic was able to improve the results in 70% (251 out of 360) of the larger instances available in the literature.