Comparison of Parallel Linear Genetic Programming Implementations
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Grochol2017,
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author = "David Grochol and Lukas Sekanina",
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title = "Comparison of Parallel Linear Genetic Programming
Implementations",
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booktitle = "Proceedings of the 22nd International Conference on
Soft Computing (MENDEL 2016)",
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year = "2016",
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editor = "Radek Matousek",
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volume = "576",
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series = "AISC",
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pages = "64--76",
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address = "Brno, Czech Republic",
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month = jun # " 8-10",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, parallel GP",
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isbn13 = "978-3-319-58087-6",
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ISSN = "2194-5357",
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DOI = "doi:10.1007/978-3-319-58088-3_7",
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abstract = "Linear genetic programming (LGP) represents candidate
programs as sequences of instructions for a register
machine. In order to accelerate the evaluation time of
candidate programs and reduce the overall time of
evolution, we propose various parallel implementations
of LGP suitable for the current multi-core processors.
The implementations are based on a parallel evaluation
of candidate programs and the island model of the
parallel evolutionary algorithm in which the
subpopulations are evolved independently, but some
genetic material can be exchanged by means of the
migration. Proposed implementations are evaluated using
three symbolic regression problems and a hash function
design problem.",
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notes = "https://link.springer.com/book/10.1007/978-3-319-58088-3
ICSC-MENDEL 2016 Recent Advances in Soft Computing",
- }
Genetic Programming entries for
David Grochol
Lukas Sekanina
Citations