A Fair Performance Comparison of Different Surrogate Optimization Strategies

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{6349,

• 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 optimization",
• 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

Citations