Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm

ABSTRACT

This article proposes an adaptive dragonfly algorithm (DA) for the structural optimization of frame structures. This algorithm, named the Coulomb force search strategy-based dragonfly algorithm (CFSSDA), combines the Coulomb force search strategy (CFSS) with the DA method. The CFSS is applied to automatically determine an adaptive search step in each iteration, thus enhancing the exploration capability of the CFSSDA. The performance of the CFSSDA is investigated on the basis of three widely used benchmark numerical examples. The results indicate that the proposed CFSSDA achieves a markedly improved convergence rate while maintaining a high accuracy. Furthermore, the CFSSDA is utilized to find the optimal parameters for an engineering frame structure problem with discrete variables under stress constraints. These results also show that the CFSSDA can rapidly generate an optimal structure with a weight that is reduced by 27.97% compared with the initial design.

KEYWORDS:

• Adaptive dragonfly algorithm
• Coulomb force search strategy
• structural optimization
• stress constraints

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number U1608256].