Evolutionary design of Evolutionary Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Diosan:2009:GPEM,
  author =       "Laura Diosan and Mihai Oltean",
  title =        "Evolutionary design of Evolutionary Algorithms",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2009",
  volume =       "10",
  number =       "3",
  pages =        "263--306",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, Evolving
                 evolutionary algorithms, Meta genetic programming,
                 Function optimization",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-009-9081-6",
  abstract =     "Manual design of Evolutionary Algorithms (EAs) capable
                 of performing very well on a wide range of problems is
                 a difficult task. This is why we have to find other
                 manners to construct algorithms that perform very well
                 on some problems. One possibility (which is explored in
                 this paper) is to let the evolution discover the
                 optimal structure and parameters of the EA used for
                 solving a specific problem. To this end a new model for
                 automatic generation of EAs by evolutionary means is
                 proposed here. The model is based on a simple Genetic
                 Algorithm (GA). Every GA chromosome encodes an EA,
                 which is used for solving a particular problem. Several
                 Evolutionary Algorithms for function optimization are
                 generated by using the considered model. Numerical
                 experiments show that the EAs perform similarly and
                 sometimes even better than standard approaches for
                 several well-known benchmarking problems.",
}

Genetic Programming entries for Laura Diosan Mihai Oltean

Citations