Sizing optimization of skeletal structures using teaching-learning based optimization
DOI:
https://doi.org/10.11121/ijocta.01.2017.00309Keywords:
Optimization, skeletal structures, teaching-learning based optimization, teaching factor, penalty functionAbstract
Teaching Learning Based Optimization (TLBO) is one of the non-traditional techniques to simulate natural phenomena into a numerical algorithm. TLBO mimics teaching learning process occurring between a teacher and students in a classroom. A parameter named as teaching factor, TF, seems to be the only tuning parameter in TLBO. Although the value of the teaching factor, TF, is determined by an equation, the value of 1 or 2 has been used by the researchers for TF. This study intends to explore the effect of the variation of teaching factor TF on the performances of TLBO. This effect is demonstrated in solving structural optimization problems including truss and frame structures under the stress and displacement constraints. The results indicate that the variation of TF in the TLBO process does not change the results obtained at the end of the optimization procedure when the computational cost of TLBO is ignored.
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