Parthasarathy D, Schmitt J, Köstler H (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: Association for Computing Machinery, Inc
Pages Range: 615-618
Conference Proceedings Title: GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion
Event location: Lisbon, PRT
ISBN: 9798400701207
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.
APA:
Parthasarathy, D., Schmitt, J., & Köstler, H. (2023). Evolving Nonlinear Multigrid Methods With Grammar-Guided Genetic Programming. In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 615-618). Lisbon, PRT: Association for Computing Machinery, Inc.
MLA:
Parthasarathy, Dinesh, Jonas Schmitt, and Harald Köstler. "Evolving Nonlinear Multigrid Methods With Grammar-Guided Genetic Programming." Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion, Lisbon, PRT Association for Computing Machinery, Inc, 2023. 615-618.
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