A new Hybrid Taguchi-salp swarm optimization algorithm for the robust design of real-world engineering problems

Abstract

In this paper, a new hybrid Taguchi salp swarm algorithm (HTSSA) has been developed to speed up the optimization processes of structural design problems in industry and to approach a global optimum solution. The design problem is posed for the shape optimization of a seat bracket with a mass objective function and a stress constraint. Objective function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations necessary for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm and, Harris hawks optimization algorithm are used to compare the performance of the HTSSA in solving the structural design problem. The results show the hybrid Taguchi salp swarm algorithm's ability and the superiority of the method developed for optimum product design processes.