Parallel genetic algorithm finding optimal initial mesh for three dimensional self-adaptive hp finite element method

Anna Paszyńska¹, Maciej Paszyński²

¹Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Reymonta 4, 30-059 Kraków, Poland.
²Department of Computer Science, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland.

DOI:

https://doi.org/10.7494/cmms.2011.1.0309

Abstract:

In this paper we investigate the parallel version of the hierarchical chromosome based genetic algorithm (HCBGA) for finding the optimal initial mesh for self-adaptive hp-Finite Element Method (hp-FEM). The HCBGA algorithm solves the global optimization problem of r refinements in order to provide optimal starting mesh for the hp-FEM that will fit material data and singularities, and will result in the exponential convergence of the hp-FEM. The parallel algorithm is tested on the damaged Step-and-Flash Imprint Lithography problem, modeled by linear elasticity with thermal expansion coefficient.

Cite as:

Paszyńska, A., & Paszyński, M. (2011). Parallel genetic algorithm finding optimal initial mesh for three dimensional self-adaptive hp finite element method. Computer Methods in Materials Science, 11(1), 34 – 40. https://doi.org/10.7494/cmms.2011.1.0309

Article (PDF):

Keywords:

Genetic algorithms, Parallel computing, Hp-finite element method

References:

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