"A Heuristic Oriented Racing Algorithm for the Fine-tuning of Metaheuristics" Eduardo B. M. Barbosa and Edson L. F. Senne The metaheuristics have become a powerful tool to solve real-world optimization problems. Its ease adaptability, usually demands effort to correctly define the design options and parameters to achieve their best performance. Thus, this paper aims to present an approach on the fine-tuning of metaheuristics combining Design of Experiments and Racing algorithms. The key idea is a heuristic method, which explores a search space of parameters, looking for candidate configurations near of a promising alternative and consistently finds the good ones. To confirm this approach, we present a case study for fine-tuning a VNS metaheuristic on the classical Traveling Salesman Problem, and compare its results against a well established racing method. In general, our approach proved to be effective in terms of the overall time of the tuning process.