The influence of population genetics for the redesign of genetic algorithms

This contribution considers recent results of population genetics in order to present generic extensions to the general concept of a Genetic Algorithm (GA). Consequently a new model for self-adaptive selection pressure steering is presented (Offspring Selection), taking advantage of the interplay between directed genetic drift and selection, resulting in a new class of Genetic Algorithms. As a result we introduce and empirically analyze the generic extensions to the general GA concept, which make genetic search more stable in terms of operators, and allows steering and scaling up of global solution quality to highest quality regions without using problem specific information or local searches.