Particular fine-grained parallel GA for simulation study of distributed human-based GA
Junya Okano, Kota Hamano, Kei Ohnishi, Mario Köppen · 2014
The paper proposes and investigates a particular fine-grained parallel genetic algorithm (GA) for understanding the behaviors of a similar distributed human-based GA through simulations. The particular fine-grained parallel GA restricts interactions between individuals in terms of not space but time, which can occur in real human interactions. Specifically, it gives each individual its own cycle time for encountering other individuals according to a probability distribution. The simulation results show that the GA performance depends on the setting of the encounter timings for the individuals.