Genetic-Algorithm Programming Environments

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{RibeiroFilho:1994:GPE,
  author =       "Jose L. {Ribeiro Filho} and Philip C. Treleaven and 
                 Cesare Alippi",
  title =        "Genetic-Algorithm Programming Environments",
  journal =      "Computer",
  volume =       "27",
  number =       "6",
  pages =        "28",
  month =        jun,
  year =         "1994",
  keywords =     "genetic algorithms, genetic programming, PC/Beagle,
                 algorithm-oriented systems, application-oriented
                 systems, generational replacement policy,
                 genetic-algorithm programming environments,
                 population-handling technique, steady-state policy,
                 toolkits, application generators, mathematics
                 computing, programming environments, search problems",
  CODEN =        "CPTRB4",
  ISSN =         "0018-9162",
  bibdate =      "Tue May 14 16:20:44 MDT 1996",
  acknowledgement = ack-nhfb,
  DOI =          "doi:10.1109/2.294850",
  size =         "16 pages",
  abstract =     "This review classifies genetic-algorithm environments
                 into application-oriented systems, algorithm-oriented
                 systems, and toolkits. It also presents detailed case
                 studies of leading environments. Following Holland's
                 (1975) original genetic algorithm proposal, many
                 variations of the basic algorithm have been introduced.
                 However. an important and distinctive feature of all
                 GAs is the population-handling technique. The original
                 GA adopted a generational replacement policy, according
                 to which the whole population is replaced in each
                 generation. Conversely, the steady-state policy used by
                 many subsequent GAs selectively replaces the
                 population. After we introduce GA models and their
                 programming, we present a survey of GA programming
                 environments. We have grouped them into three major
                 classes according to their objectives:
                 application-oriented systems hide the details of GAs
                 and help users develop applications for specific
                 domains; algorithm-oriented systems are based on
                 specific GA models; and toolkits are flexible
                 environments for programming a range of GAs and
                 applications. We review the available environments and
                 describe their common features and requirements. As
                 case studies, we select some specific systems for more
                 detailed examination. To conclude, we discuss likely
                 future developments in GA programming environments",
  notes =        "Zeluiz Also known as \cite{294850}",
}

Genetic Programming entries for Jose L Ribeiro Filho Philip Treleaven Cesare Alippi

Citations