Due to the stochastic characteristics of bio-inspired optimization algorithms, several executions are often required; then a suitable infrastructure must be available to run these algorithms. This paper reviews a virtualized distributed processing scheme to establish an adequate infrastructure for the execution of bio-inspired algorithms. In order to test the virtualized distributed system, the well known versions of genetic algorithms, differential evolution and particle swarm optimization, are used. The results show that the revised distributed virtualized schema allows speeding up the execution of the algorithms without altering their result in the objective function.