Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm. Issue 6 (2nd June 2020)

• Record Type: Journal Article
• Authors: Yuan, Yongliang; Lv, Liye; Wang, Xiaobang; Song, Xueguan
• Is Part Of: Engineering optimization. Volume 52:Issue 6(2020)
• Page Start: 915
• Page End: 931
• Publication Date: 2020-06-02
• Subjects: Adaptive dragonfly algorithm -- Coulomb force search strategy -- structural optimization -- stress constraints; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2019.1618290
• Languages: English
• ISSNs: 0305-215X

Abstract

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.