A Distance Between Populations for n-Points Crossover in Genetic Algorithms
Neural and Evolutionary Computing
2017-07-04 v1
Abstract
Genetic algorithms (GAs) are an optimization technique that has been successfully used on many real-world problems. There exist different approaches to their theoretical study. In this paper we complete a recently presented approach to model one-point crossover using pretopologies (or Cech topologies) in two ways. First, we extend it to the case of n-points crossover. Then, we experimentally study how the distance distribution changes when the number of crossover points increases.
Keywords
Cite
@article{arxiv.1707.00451,
title = {A Distance Between Populations for n-Points Crossover in Genetic Algorithms},
author = {Mauro Castelli and Gianpiero Cattaneo and Luca Manzoni and Leonardo Vanneschi},
journal= {arXiv preprint arXiv:1707.00451},
year = {2017}
}