Evolving Nonlinear Multigrid Methods With Grammar-Guided Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{parthasarathy:2023:GECCOcomp,

• author = "Dinesh Parthasarathy and Jonas Schmitt and Harald Koestler",
• title = "Evolving Nonlinear Multigrid Methods With {Grammar-Guided} Genetic Programming",
• booktitle = "Proceedings of the 2023 Genetic and Evolutionary Computation Conference",
• year = "2023",
• editor = "Sara Silva and Luis Paquete and Leonardo Vanneschi and Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and Arnaud Liefooghe and Bing Xue and Ying Bi and Nelishia Pillay and Irene Moser and Arthur Guijt and Jessica Catarino and Pablo Garcia-Sanchez and Leonardo Trujillo and Carla Silva and Nadarajen Veerapen",
• pages = "615--618",
• address = "Lisbon, Portugal",
• series = "GECCO '23",
• month = "15-19 " # jul,
• organisation = "SIGEVO",
• publisher = "Association for Computing Machinery",
• publisher_address = "New York, NY, USA",
• keywords = "genetic algorithms, genetic programming, grammar-guided genetic programming, code generation, nonlinear multigrid methods: Poster",
• isbn13 = "9798400701191",
• DOI = "doi:10.1145/3583133.3590734",
• size = "4 pages",
• abstract = "We formulate a formal grammar to generate Full Approximation Scheme multigrid solvers. Then, using Grammar-Guided Genetic Programming we perform a multiobjective optimization to find optimal instances of such solvers for a given nonlinear system of equations. This approach is evaluated for a two-dimensional Poisson problem with added nonlinearities. We observe that the evolved solvers outperform the baseline methods by having a faster runtime and a higher convergence rate.",
• notes = "GECCO-2023 A Recombination of the 32nd International Conference on Genetic Algorithms (ICGA) and the 28th Annual Genetic Programming Conference (GP)",

}

Genetic Programming entries for Dinesh Parthasarathy Jonas Schmitt Harald Koestler

Citations