Analysis of implicit parallelism in evolutionary algorithms: a stochastic version

Abstract

Implicit parallelism in evolutionary algorithms is discussed. Under the condition of sampling populations with equal probability, an accurate expression of the expected number of different schemata processed by the evolutionary algorithms in each generation is obtained. Moreover, some kinds of the upper and lower bounds of the expected number are estimated.