Hull optimization plays a crucial role in enhancing ship performance and efficiency. This study aimed to improve ship performance, particularly by reducing total resistance, through automated optimization methods. To this end, an integrated, fully automated optimization program was developed based on Python, incorporating Enhanced Free-Form Deformation (FFD) technology, scripted CFD numerical evaluation, and the Particle Swarm Optimization (PSO) algorithm. This program allowed precise control of hull form, improving efficiency while reducing costs. The KCS hull, known for its excellent resistance performance, was chosen as the optimization target, with the goal of minimizing total resistance by adjusting the bulbous bow line plan. The research results indicated that the optimized scheme exhibited lower resistance characteristics compared to the original design while satisfying design constraints. This study not only provides a new optimization strategy for ship design but also lays a foundation for future hull optimization research.
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