Crashworthiness and lightweight design are two main challenges in the early body in white (BIW) design stage. An implicit parametric model of BIW was built by using SFE-CONCEPT to allow for larger geometrical modifications and more flexible design space. A physical test was then conducted to verify the validity of the implicit parametric model. A hybrid method coupling the particle swarm optimization (PSO) algorithm with the bacterial foraging optimization (BFO) algorithm has been proposed to improve the crashworthiness and lightweight design. This method aims to obtain the Pareto sets to guide designers in selecting the optimal solution according to different demand. Meanwhile, a comparison between the proposed hybrid method and other widely used intelligent methods (PSO, BFO, and PSO–GA) was performed to illustrate the advantages of the hybrid method in solving complex, nonlinear, and multi-objective optimization problems. The results indicate that the proposed hybrid method has significant potential to optimize the crashworthiness and to guide lightweight design of BIW.
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