Combining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3989

@InCollection{Kaufmann:2017:miller,
  author =       "Paul Kaufmann and Marco Platzner",
  title =        "Combining Local and Global Search: A Multi-objective
                 Evolutionary Algorithm for Cartesian Genetic
                 Programming",
  booktitle =    "Inspired by Nature: Essays Presented to Julian F.
                 Miller on the Occasion of his 60th Birthday",
  publisher =    "Springer",
  year =         "2017",
  editor =       "Susan Stepney and Andrew Adamatzky",
  volume =       "28",
  series =       "Emergence, Complexity and Computation",
  chapter =      "8",
  pages =        "175--194",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming",
  isbn13 =       "978-3-319-67996-9",
  DOI =          "doi:10.1007/978-3-319-67997-6_8",
  abstract =     "This work investigates the effects of the
                 periodization of local and global multi-objective
                 search algorithms. We rely on a model for periodization
                 and define a multi-objective evolutionary algorithm
                 adopting concepts from Evolutionary Strategies and
                 NSGAII. We show that our method excels for the
                 evolution of digital circuits on the Cartesian Genetic
                 Programming model as well as on some standard
                 benchmarks such as the ZDT6, especially when periodized
                 with standard multi-objective genetic algorithms.",
  notes =        "part of \cite{miller60book}
                 https://link.springer.com/bookseries/10624",
}

Genetic Programming entries for Paul Kaufmann Marco Platzner

Citations