Genetic programming with multiple initial populations generated by simulated annealing
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Mototsuka:2013:IWCIA,
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author = "Takuya Mototsuka and Akira Hara and
Jun-ichi Kushida and Tetsuyuki Takahama",
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title = "Genetic programming with multiple initial populations
generated by simulated annealing",
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booktitle = "Sixth IEEE International Workshop on Computational
Intelligence Applications (IWCIA 2013)",
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year = "2013",
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month = "13 " # jul,
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pages = "113--118",
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keywords = "genetic algorithms, genetic programming, simulated
Annealing Programming, Evolutionary Computation",
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DOI = "doi:10.1109/IWCIA.2013.6624797",
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ISSN = "1883-3977",
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abstract = "Genetic Programming (GP) and Simulated Annealing
Programming (SAP) are typical metaheuristic methods for
automatic programming. We propose a new method,
Parallel - Genetic and Annealing Programming (P-GAP)
which combines GP and SAP. In P-GAP, multiple initial
populations are generated by SAP. Respective
populations evolve by parallel GP. As the generation
proceeds, populations are integrated gradually. To
examine the effectiveness, we compared P-GAP with the
conventional methods in five test problems. As a
result, P-GAP showed better performance than GP and
SAP.",
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notes = "Also known as \cite{6624797}",
- }
Genetic Programming entries for
Takuya Mototsuka
Akira Hara
Jun-ichi Kushida
Tetsuyuki Takahama
Citations