Genetic programming with multiple initial populations generated by simulated annealing

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Mototsuka:2013:IWCIA,

• author = "Takuya Mototsuka and Akira Hara and Jun-ichi Kushida and Tetsuyuki Takahama",
• title = "Genetic programming with multiple initial populations generated by simulated annealing",
• booktitle = "Sixth IEEE International Workshop on Computational Intelligence Applications (IWCIA 2013)",
• year = "2013",
• month = "13 " # jul,
• pages = "113--118",
• keywords = "genetic algorithms, genetic programming, simulated Annealing Programming, Evolutionary Computation",
• DOI = "doi:10.1109/IWCIA.2013.6624797",
• ISSN = "1883-3977",
• 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.",
• notes = "Also known as \cite{6624797}",

}

Genetic Programming entries for Takuya Mototsuka Akira Hara Jun-ichi Kushida Tetsuyuki Takahama

Citations