With the rapid development of global trade and the continuous growth of the marine economy, ships, as an important logistics tool, play an increasingly important role in China's economic development, and their operational efficiency and safety are receiving more and more attention. Spare parts for ships are vital to ensure that the ship operates properly and is functional underway. Ships will stock a certain amount of spare parts to minimize ship downtime for maintenance. Therefore, accurate configuration is required for spare parts management to ensure instant access to the required parts during ship maintenance. To achieve this goal, we propose a ship spare parts allocation optimization method based on a single-objective multi-objective particle swarm algorithm. First, the ship spare parts allocation optimization model is constructed. Second, single-objective and multi-objective particle swarm optimization techniques are used to solve the model and optimize the ship's non-low-demand spare parts allocation. Finally, Monte Carlo simulation is used to verify the feasibility of the configuration optimization method.