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

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

@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