The hydrodynamic optimization of containership hull forms is critical for enhancing hydrodynamic performance, reducing fuel consumption, and achieving compliance with energy efficiency standards. This study introduces an automated, computationally efficient optimization framework that integrates a parametric hull form optimization process with a weak-scatterer approach for minimizing ship resistance in calm water and wave conditions. Using a fully parametric modeling framework, the hull geometry is flexibly adjusted during optimization, which is conducted via the surrogate-based global optimization algorithm. Hydrodynamic performance is assessed through a weak-scatterer approach, an efficient weakly nonlinear model grounded in potential-flow theory, with results validated against computational fluid dynamics methods (STAR-CCM+) and experimental data. By integrating modeling, simulation, and optimization modules, the developed optimization framework enables streamlined optimization analysis and design iterations. The optimized hull forms achieve notable reductions in wave-making and wave-added resistance, contributing to improved fuel efficiency and reduced environmental impact. This work advances the state of the art in sustainable ship design by addressing the critical challenge of balancing computational efficiency with performance optimization across diverse maritime conditions.
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Feng et al. (2025) studied this question.