Mapping evolutionary algorithms to a reactive, stateless architecture
Juan Julián Merelo, Mario García-Valdéz · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2018
Genetic algorithms (GA) [8] are currently one of the most widely used meta-heuristics to solve engineering problems. Furthermore, parallel genetic algorithms (pGAs) are useful to find solutions of complex optimizations problems in adequate times [16]; in particular, problems with complex fitness. Some authors [1] state that using pGAs improves the quality of solutions in terms of the number of evaluations needed to find one. This reason, together with the improvement in evaluation time brought by the simultaneous running in several nodes, have made parallel and distributed evolutionary algorithms a popular methodology.