http://opendata.unex.es/recurso/ciencia-tecnologia/investigacion/publicaciones/Publicacion/2019-3748

Literals

  • ou:bibtex
    • @Article{mca24030078,AUTHOR={Juárez-Smith, Perla and Trujillo, Leonardo and García-Valdez, Mario and Fernández de Vega, Francisco and Chávez, Francisco},TITLE={Pool-Based Genetic Programming Using Evospace, Local Search and Bloat Control},JOURNAL={Mathematical and Computational Applications},VOLUME={24},YEAR={2019},NUMBER={3},ARTICLE-NUMBER={78},URL={https://www.mdpi.com/2297-8747/24/3/78},ISSN={2297-8747},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 behavior of the search was analyzed 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.},DOI={10.3390/mca24030078}}
  • dcterms:contributor
    • Juárez-Smith, Perla, Trujillo, Leonardo, García-Valdez, Mario, Fernández de Vega, Francisco, Chávez, Francisco
  • bibo:doi
    • 10.3390/mca24030078
  • fabio:hasPublicationYear
    • 2019
  • vivo:identifier
    • 2019-3748
  • bibo:issn
    • 2297-8747
  • ou:tipoPublicacion
    • Article
  • dcterms:title
    • Pool-Based Genetic Programming Using Evospace, Local Search and Bloat Control
  • vcard:url
  • ou:urlOrcid

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