Volume 8, Number 2 (8-2018)                   2018, 8(2): 227-246 | Back to browse issues page

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Abstract:   (171 Views)
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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Type of Study: Research | Subject: Optimal design
Received: 2017/08/26 | Accepted: 2017/08/26 | Published: 2017/08/26