This paper presents nn ca parallel genetic algorithm for finding near optimal solutions to the well-known traveling salesman problem, in a distributed computational environment. The proposed algorithm, called Grisland, combines two well known parallel genetic algorithms: the Grid genetic algorithm (fine grained model) and the Island genetic algorithm, and is improved with a local optimization technique, called 2-opt, especially developed for the traveling salesman problem. The proposed algorithm is tested on a subset of the standard TSPLib data set. Our results show that GridsLand is able to find good solutions for the Traveling Salesman Problem in few parallel iterations of the evolutionary process.