Develop, Deploy and Execute Parallel Genetic Algorithms in the Cloud

Making Genetic Algorithms (GAs) distributed in an on-demand fashion involves different phases from resources allocation to actual deployment and execution. We propose a cloud architecture with a conceptual workflow able to cover each GAs distribution phase.