An Island Model based on Stigmergy to solve optimization problems

Island Model (IM) is an alternative often used to parallel Evolutionary Algorithms (EA). In IM, the population is distributed between islands that evolve their solutions in parallel, connected by a topology. Periodically, solutions migrate between islands according to a migration policy. The IM can be seen as an ideal structure to combine different algorithms to be used in an organized and cooperative way to solve a problem. Motivated by the number and distinction of EAs proposed in the last decades, in terms of performance and evolutionary behavior, this work proposes a hybrid configuration for IM, called Stigmergy Island Model (Stgm-IM), inspired by the natural phenomenon of stigmergy. Stigmergy is present in groups of some social species, and, by it, their agents organize themselves and maintain a level of cooperation through indirect communication. The Stgm-IM was evaluated regarding its evolutionary behavior and its performance on a benchmark suite of fifteen optimization problems, showing expected results.