Abstract. In this paper, we apply a competitive coevolutionary approach using loosely coupled genetic algorithms to a distributed optimization of the Rosenbrock's function. The computational scheme is a coevolutionary system of agents with only local interaction among them, without any central synchronization. We use a recently developed coordination language called Manifold to implement our distributed optimization algorithm. We show that the distributed optimization algorithm implemented using Manifold outperforms the sequential optimization algorithm based on a standard genetic algorithm.