Pool-Based Genetic Programming Using Evospace, Local Search and Bloat Control
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{juarez-smith:2019:MCA,
-
author = "Perla Juarez-Smith and Leonardo Trujillo and
Mario Garcia-Valdez and Francisco {Fernandez de Vega} and
Francisco Chavez",
-
title = "{Pool-Based} Genetic Programming Using Evospace, Local
Search and Bloat Control",
-
journal = "Mathematical and Computational Applications",
-
year = "2019",
-
volume = "24",
-
number = "3",
-
keywords = "genetic algorithms, genetic programming",
-
ISSN = "2297-8747",
-
URL = "https://www.mdpi.com/2297-8747/24/3/78",
-
DOI = "doi:10.3390/mca24030078",
-
abstract = "This work presents a unique genetic programming (GP)
approach that integrates a numerical local search
method and a bloat-control mechanism within a
distributed model for evolutionary algorithms known as
EvoSpace. The first two elements provide a directed
search operator and a way to control the growth of
evolved models, while the latter is meant to exploit
distributed and cloud-based computing architectures.
EvoSpace is a Pool-based Evolutionary Algorithm, and
this work is the first time that such a computing model
has been used to perform a GP-based search. The
proposal was extensively evaluated using real-world
problems from diverse domains, and the behaviour of the
search was analysed from several different
perspectives. The results show that the proposed
approach compares favorably with a standard approach,
identifying promising aspects and limitations of this
initial hybrid system.",
-
notes = "also known as \cite{mca24030078}",
- }
Genetic Programming entries for
Perla Sarahi Juarez-Smith
Leonardo Trujillo
Mario Garcia-Valdez
Francisco Fernandez de Vega
Francisco Chavez de la O
Citations