Increasing Diversity and Controlling Bloat in Linear Genetic Programming

Abstract

The objective of this paper is to use the age-layered population structure model to increase diversity and control bloat of the population in linear genetic programming. Firstly, we use two level tournament selection to increase the sub-population diversity in each layer, and then apply the new model to linear genetic programming to increase the sub-population and the entire population diversity. The age-layered population structure model segregates individuals into different age-layers by their age, so it limits the quantity of the old age and long length individuals. Besides, the model regularly introduces new randomly generated short individuals into the youngest layer to reduce the average length of the population. The experimental results show that the age-layered population structure model can increase diversity and control bloat of the population effectively.