A new chaotic Levy flight distribution optimization algorithm for solving constrained engineering problems

This work proposed a new metaheuristic dubbed as Chaotic Levy flight distribution (CLFD) algorithm, to address physical world engineering optimization problems that incorporate the chaotic maps in the elementary Levy flight distribution (LFD). Hybridization aims to increase the LFD rate of convergence while also providing a problem-free optimization approach. The proposed methodology is investigated for five case studies of constrained optimization issues followed by shape optimization of structural design. The outcomes from the CFLD algorithm are further contrasted with its fundamental version and other distinguished recently introduced algorithms. The computational analysis illustrates the dominance of CLFD over other considered optimizers. Moreover, the present investigation shows that CLFD is a robust technique that can efficiently find optimal mechanical design problems with a proper chaotic map selection.

Automated summary

This paper proposes a new metaheuristic algorithm called Chaotic Levy flight distribution (CLFD) algorithm, which is aimed at solving engineering optimization problems in the physical world. The results of the study show that CLFD algorithm has advantages in solving optimization problems and can effectively find optimal solutions.