Distributed genetic programming for obtaining formulas: Application to concrete strength

Abstract

This paper presents a Genetic Programming algorithm which applies a clustering algorithm. The method evolves a population of trees for a fixed number of rounds or generations and applies a clustering algorithm to the population, in a way that in the selection process of trees their structure is taken into account. The proposed method, named DistClustGP, runs in a parallel environment, according to the model master-slave, so that it can evolve simultaneously different populations, and evolve together the best individuals from each cluster. DistClustGP favors the analysis of the parameters involved in the genetic process, decreases the number of generations necessary to obtain satisfactory results through evolution of different populations, due to its parallel nature, and allows the evolution of the best individuals taking into account their structure. © 2010 Springer-Verlag Berlin Heidelberg.