Genetic Algorithms (GAs) are a powerful technique to address hard optimisation problems.
However, scalability issues might prevent them from being applied to real-world problems.
Exploiting parallel GAs in the cloud might be an affordable approach to get time efficient
solutions that benefit of the appealing features of the cloud, such as scalability, reliability,
fault-tolerance and cost-effectiveness. Nevertheless, distributed computation is very prone to
cause considerable overhead for communication and making GAs distributed in an on …