<p>In formula-racing car design, lightweight chassis is of paramount significance. Given the complexity of the racing environment and the multitude of loads acting on vehicles, research on multi-objective topology optimization for chassis remains relatively sparse. This study endeavors to synthesize the entropy weight method (EWM) and analytic hierarchy process (AHP) to formulate a multi-objective topology optimization framework tailored specifically for the formula one racing car chassis. Through the implementation of a hybridized approach amalgamating these methodologies, the optimal weight combinations for the chassis across varying operational conditions were ascertained and amalgamated into a holistic objective function aimed at achieving chassis topology optimization. The findings of this investigation reveal pronounced advantages following chassis topology optimization employing the hybrid strategy, including noteworthy enhancements in both strength and stiffness, discernible augmentation in lower-order natural frequencies, and corresponding reduction in higher-order natural frequencies. Such advancements significantly contribute to the amelioration of a vehicle’s dynamic performance and attenuation of vibrations and noise, thereby bolstering its overall operational efficacy. This study not only introduces novel conceptual frameworks and methodologies for the lightweight design and multi-objective topology optimization of formula-racing cars but also serves to advance the widespread application and further refinement of multi-objective optimization theory within the realm of practical engineering challenges.</p>