A Fair Performance Comparison of Different Surrogate Optimization Strategies

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Bernhard Werth and Erik Pitzer and 
                 Michael Affenzeller",
  title =        "A Fair Performance Comparison of Different Surrogate
                 Optimization Strategies",
  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 =        "408--415",
  address =      "Las Palmas de Gran Canaria, Spain",
  month =        feb,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Surrogate
                 models, Evolutionary algorithms, Black-box
  isbn13 =       "978-3-319-74718-7",
  URL =          "https://link.springer.com/chapter/10.1007/978-3-319-74718-7_49",
  DOI =          "doi:10.1007/978-3-319-74718-7_49",
  size =         "8",
  abstract =     "Much of the literature found on surrogate models
                 presents new approaches or algorithms trying to solve
                 black-box optimization problems with as few evaluations
                 as possible. The comparisons of these new ideas with
                 other algorithms are often very limited and constrained
                 to non-surrogate algorithms or algorithms following
                 very similar ideas as the presented ones. This work
                 aims to provide both an overview over the most
                 important general trends in surrogate assisted
                 optimization and a more wide-spanning comparison in a
                 fair environment by reimplementation within the same
                 software framework.",
  notes =        "Published 2018?",

Genetic Programming entries for Bernhard Werth Erik Pitzer Michael Affenzeller