Adaptive Gene Level Mutation
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- @Article{al-afandi:2021:Algorithms,
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author = "Jalal Al-Afandi and Andras Horvath",
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title = "Adaptive Gene Level Mutation",
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journal = "Algorithms",
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year = "2021",
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volume = "14",
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number = "1",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "1999-4893",
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URL = "https://www.mdpi.com/1999-4893/14/1/16",
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DOI = "doi:10.3390/a14010016",
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abstract = "Genetic Algorithms are stochastic optimisation methods
where solution candidates, complying to a specific
problem representation, are evaluated according to a
predefined fitness function. These approaches can
provide solutions in various tasks even, where analytic
solutions can not be or are too complex to be computed.
In this paper we will show, how certain set of problems
are partially solvable allowing us to grade segments of
a solution individually, which results local and
individual tuning of mutation parameters for genes. We
will demonstrate the efficiency of our method on the
N-Queens and travelling salesman problems where we can
demonstrate that our approach always results faster
convergence and in most cases a lower error than the
traditional approach.",
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notes = "also known as \cite{a14010016}",
- }
Genetic Programming entries for
Jalal Al-Afandi
Andras Horvath
Citations