Optimized Design of Tube Hydroforming Loading Path Using Multi-Objective Differential Evolution


Loading path design is one of the main factors that influence the quality of tube hydroforming processes. The conflicts between different quality indicators can be solved using multi-objective optimization evolutionary algorithms. In this paper, we propose a multi-objective optimization using differential evolution to obtain the optimum cooperation between the internal pressure and end feeding process. In the optimization process, several finite element simulations are performed to set up a least-squares support vector machine-based response surface model, which significantly improves the accuracy. We used a pre-bent hydroforming case study to demonstrate that this method is effective, accurate, and reliable.