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Topology optimisation using MPBILs and multi-grid ground element

Author(s)
Sleesongsom, Suwin
Bureerat, Sujin
Date Issued
February 12, 2018
Type
Article
DOI
10.3390/app8020271
Abstract
This paper aims to study the comparative performance of original multi-objective population-based incremental learning (MPBIL) and three improvements of MPBIL. The first improvement of original MPBIL is an opposite-based concept, whereas the second and third method enhance the performance of MPBIL using the multi and adaptive learning rate, respectively. Four classic multi-objective structural topology optimization problems are used for testing the performance. Furthermore, these topology optimization problems are improved by the method of multiple resolutions of ground elements, which is called a multi-grid approach (MG). Multi-objective design problems with MG design variables are then posed and tackled by the traditional MPBIL and its improved variants. The results show that using MPBIL with opposite-based concept and MG approach can outperform other MPBIL versions.
Citation
Applied Sciences Switzerland, 8(2), 2018
Subjects

Adaptive learning rat...

Multi-objective optim...

Opposite-based evolut...

Population-based incr...

Topology optimization...

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