The design of unmanned surface vehicle (USV) is a complex system engineering involving multiple design contents. It is necessary to maximize the comprehensive navigation capabilities of USV while meeting the design and performance requirements. In this regard, this study conducts multi-objective optimization of the hydrodynamic performance (rapidity, seakeeping, overturning resistance, and maneuverability) of a catamaran USV. Aiming at the shortcomings of ordinary particle swarm optimization (PSO) algorithm, such as easy to fall into local optimum, low convergence precision and slow convergence speed, this study proposes an improved PSO algorithm based on a hybrid strategy. After introducing the black widow optimization (BWO) movement strategy balance algorithm into the particle velocity update method, the local search and global search capabilities are improved. Then the BWO hybrid PSO algorithm is simplified by removing the particle velocity term of the particle swarm hybrid black widow evolution equation, so that the original second-order differential equation is simplified into a first-order differential equation. The evolution process is only controlled by the improved particle position, which avoids the problems of slow convergence and low accuracy in the later period due to particle divergence caused by the particle velocity term. Through comparative analysis of the algorithm optimization results and computational fluid dynamics (CFD) simulation verification, the results show that the simplified BWO hybrid PSO algorithm has better results in multi-objective optimization of the hydrodynamic performance of the catamaran USV.