Optimizing Maritime Propeller Design with Continuous Evolutionary Algorithms

The vessels are powered by propellers that convert engine power into movement. Optimizing propeller design involves numerous variables like diameter and blade count, making exact methods impractical. Meta-heuristics, such as evolutionary algorithms, offer a promising solution. This study introduces a novel marine propeller optimization approach. It decomposes the optimization process and proposes a new fitness function to overcome previous limitations. Based on two continuous optimization algorithms, the approach was compared to the state-of-the-art differential evolution algorithm. Results from ferry-boat propeller design experiments show the proposed approach achieves approximately 1% higher efficiency than the baseline study at 7.0 and 7.5-knot speeds. The proposed approach succeeds at 8.0 and 8.5 knots, where the baseline failed. Additionally, decomposition reduces execution time by executing in six threads.