The Team Orienteering Problem (TOP) is a variant of the vehicle routing problem. Given a set of vertices, each one associated with a score, the goal of TOP is to maximize the sum of the scores collected by a xed number of vehicles within a certain prescribed time limit. More particularly, the Team Orienteering Problem with Time Windows (TOPTW) imposes the period of time of customer availability as a constraint to assimilate the real world situations. In this paper, we present a memetic algorithm for TOPTW based on the application of split strategy to evaluate an individual. The eff ectiveness of the proposed MA is shown by many experiments conducted on benchmark problem instances available in the literature. The computational results indicate that the proposed algorithm competes with the heuristic approaches present in the literature and improves best known solutions in 101 instances.