Experimental Analysis of the Tournament Size on Genetic Algorithms
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- @InProceedings{Lavinas:2018:ieeeSMC,
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author = "Yuri Lavinas and Claus Aranha and Tetsuya Sakurai and
Marcelo Ladeira",
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booktitle = "2018 IEEE International Conference on Systems, Man,
and Cybernetics (SMC)",
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title = "Experimental Analysis of the Tournament Size on
Genetic Algorithms",
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year = "2018",
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pages = "3647--3653",
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abstract = "We perform an experimental study about the effect of
the tournament size parameter from the Tournament
Selection operator. Tournament Selection is a classic
operator for Genetic Algorithms and Genetic
Programming. It is simple to implement and has only one
control parameter, the tournament size. Even though it
is commonly used, most practitioners still rely on
rules of thumb when choosing the tournament size. For
example, almost all works in the past 15 years use a
value of 2 for the tournament size, with little
reasoning behind that choice. To understand the role of
the tournament size, we run a real-valued GA on 24 BBOB
problems with 10, 20 and 40 dimensions. We also vary
the crossover operator and the generational policy of
the GA. For each combination of the above factors we
observe how the quality of the final solution changes
with the tournament size. Our findings do not support
the indiscriminate use of tournament size 2, and
recommend a more careful set up of this parameter.",
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keywords = "genetic algorithms, genetic programming, Sociology,
Statistics, Convergence, Benchmark testing, Decision
making, Next generation networking",
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DOI = "doi:10.1109/SMC.2018.00617",
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ISSN = "2577-1655",
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month = oct,
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notes = "Also known as \cite{8616614}",
- }
Genetic Programming entries for
Yuri Lavinas
Claus de Castro Aranha
Tetsuya Sakurai
Marcelo Ladeira
Citations