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Generating optimised partitions for parallel finite element computations employing float-encoded genetic algorithms

A. Rama Mohan Rao1, T.V.S.R. Appa Rao2, B. Dattaguru3

Scientist, Structural Engineering Research Centre, Chennai, India
Former Director, Structural Engineering Research Centre, Chennai, India
Chairman & Professor, Dept. Aerospace Engg., IISc, Bangalore,India

Computer Modeling in Engineering & Sciences 2004, 5(3), 213-234. https://doi.org/10.3970/cmes.2004.005.213

Abstract

This paper presents an algorithm for automatic partitioning of unstructured meshes for parallel finite element computations employing float-encoded genetic algorithms (FEGA). The problem of mesh partitioning is represented in such a way that the number of variables considered in the genome (chromosome) construction is constant irrespective of the size of the problem. In order to accelerate the computational process, several acceleration techniques like constraining the search space, local improvement after initial global partitioning have been attempted. Finally, micro float-encoded genetic algorithms have been developed to accelerate the computational process.

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APA Style
Rao, A.R.M., Rao, T.A., Dattaguru, B. (2004). Generating optimised partitions for parallel finite element computations employing float-encoded genetic algorithms. Computer Modeling in Engineering & Sciences, 5(3), 213-234. https://doi.org/10.3970/cmes.2004.005.213
Vancouver Style
Rao ARM, Rao TA, Dattaguru B. Generating optimised partitions for parallel finite element computations employing float-encoded genetic algorithms. Comput Model Eng Sci. 2004;5(3):213-234 https://doi.org/10.3970/cmes.2004.005.213
IEEE Style
A.R.M. Rao, T.A. Rao, and B. Dattaguru "Generating optimised partitions for parallel finite element computations employing float-encoded genetic algorithms," Comput. Model. Eng. Sci., vol. 5, no. 3, pp. 213-234. 2004. https://doi.org/10.3970/cmes.2004.005.213



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