Analysis and Visualization of the Impact of Different Parameter Configurations on the Behavior of Evolutionary Algorithms

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@InProceedings{6348,
  author =       "Stefan Wagner and Andreas Beham and 
                 Michael Affenzeller",
  title =        "Analysis and Visualization of the Impact of Different
                 Parameter Configurations on the Behavior of
                 Evolutionary Algorithms",
  booktitle =    "Computer Aided Systems Theory, EUROCAST 2017",
  year =         "2017",
  editor =       "Roberto Moreno-Diaz and Franz Pichler and 
                 Alexis Quesada-Arencibia",
  volume =       "10671",
  series =       "Lecture Notes in Computer Science",
  pages =        "439--446",
  address =      "Las Palmas de Gran Canaria, Spain",
  month =        feb,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-74717-0",
  URL =          "https://link.springer.com/chapter/10.1007%2F978-3-319-74718-7_53",
  DOI =          "doi:10.1007/978-3-319-74718-7_53",
  abstract =     "Evolutionary algorithms are generic and flexible
                 optimization algorithms which can be applied to many
                 optimization problems in different domains. Depending
                 on the specific type of evolutionary algorithm, they
                 offer several parameters such as population size,
                 mutation probability, crossover and mutation operators,
                 or number of elite solutions. How these parameters are
                 set has a crucial impact on the algorithm's search
                 behaviour and thus affects its performance. Therefore,
                 parameter tuning is an important and challenging task
                 in each application of evolutionary algorithms in order
                 to retrieve satisfying results.",
  notes =        "Published 2018?",
}

Genetic Programming entries for Stefan Wagner Andreas Beham Michael Affenzeller

Citations