OPTIMAL DECOMPOSITION OF FINITE ELEMENT MESHES VIA K-MEDIAN METHODOLOGY AND DIFFERENT METAHEURISTICS

Authors

  • A. Dadras
  • A. Kaveh
Abstract:

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the corresponding graph, and k-median approach is employed. The performance of these methods is investigated through four FE models with different topology and number of meshes. A comparison of the numerical results using different algorithms indicates, in most cases the BBO is capable of performing better or identical using less time with equal computational effort.

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Journal title

volume 8  issue 2

pages  227- 246

publication date 2018-08

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