Analysis and Visualization of the Impact of Different Parameter Configurations on the Behavior of Evolutionary Algorithms
Created by W.Langdon from
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- @InProceedings{6348,
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author = "Stefan Wagner and Andreas Beham and
Michael Affenzeller",
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title = "Analysis and Visualization of the Impact of Different
Parameter Configurations on the Behavior of
Evolutionary Algorithms",
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booktitle = "Computer Aided Systems Theory, EUROCAST 2017",
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year = "2017",
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editor = "Roberto Moreno-Diaz and Franz Pichler and
Alexis Quesada-Arencibia",
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volume = "10671",
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series = "Lecture Notes in Computer Science",
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pages = "439--446",
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address = "Las Palmas de Gran Canaria, Spain",
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month = feb,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-74717-0",
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URL = "https://link.springer.com/chapter/10.1007%2F978-3-319-74718-7_53",
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DOI = "doi:10.1007/978-3-319-74718-7_53",
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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.",
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notes = "Published 2018?",
- }
Genetic Programming entries for
Stefan Wagner
Andreas Beham
Michael Affenzeller
Citations