Selection pressure and takeover time of distributed evolutionary algorithms
Gabriel Luque, Enrique Alba · 2010
This paper presents a theoretical study about the selection pressure and the convergence speed of distributed evolutionary algorithms (dEA). In concrete, we model the best individual's growth curve and the takeover time for usual models of multipopulation EAs found in the literature. The calculation of the takeover time is a common analytical approach to measure the selection pressure of an EA. This work is another step forward to mathematically unify and describe the roles of all the parameters of the migration policy (the migration rate, the migration period, the topology, and the selection/replace schemes of immigrants) in the selection pressure induced by the dynamics of dEAs. In order to achieve these goals we analyze the behaviour of these algorithms and propose a mathematical formula which models that dynamic. The proposed mathematical model is later verified in practice.