基于语法导向遗传规划的非线性多网格演化方法

Proceedings of the Companion Conference on Genetic and Evolutionary Computation Pub Date : 2023-07-15 DOI:10.1145/3583133.3590734

Dinesh Parthasarathy, J. Schmitt, H. Köstler

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引用次数: 0

摘要

我们制定了一个形式化语法来生成全近似方案多网格求解器。然后，使用语法引导遗传规划，我们执行多目标优化，以找到给定非线性方程组的这种求解器的最优实例。用该方法对二维非线性泊松问题进行了评价。我们观察到，进化的求解器具有更快的运行时间和更高的收敛速度，优于基线方法。

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Evolving Nonlinear Multigrid Methods With Grammar-Guided Genetic Programming

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.

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Proceedings of the Companion Conference on Genetic and Evolutionary Computation

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