A GA-based Shape Optimizer for Underwater Vehicles

This paper proposes a non-gradient optimizer to apply to design and optimization of underwater vehicles. Alien to the traditional approaches, out optimizer employs genetic algorithm to design the underwater vehicles´ optimal shape and assembly with a given initial vehicle form. And meanwhile, a comprehensive evaluation, which may include resistance, noise, efficiency, maneuvering, etc., is elaborately considered, especially taking the hydrodynamics-related effects into account. In addition, we established the optimizer with GATBX library, Gambit, and FLUENT.