Brachistochrone-Principle-Based Adaptive Ant-Colony Algorithm for Ship Path Planning in Practical Environments

When ships navigate the ocean, the shortest route often differs significantly from the most energy-efficient path, exhibiting characteristics akin to the brachistochrone curve. To find an accurate energy-saving path for ships in complex marine environments, a route-planning algorithm based on the brachistochrone principle and the ant-colony rule is proposed in this work. First, a ship energy-consumption model is constructed, accounting for the influences of winds, waves, and currents on energy consumption, to provide the optimization target to the path-planning algorithm. Second, the ant-colony algorithm with a heuristic information function is designed based on the brachistochrone curve to form a complete optimal trajectory-design scheme. Furthermore, an adaptive mechanism is introduced into the ant-colony algorithm, including parameters, control method, and pheromone-update rule, to balance the quality and diversity of the planned paths. Simulation results demonstrate that the proposed algorithm outperforms existing methods in complex marine environments, achieving paths with 8.23% lower fuel consumption when compared with actual routes in the database. This advancement holds significant practical value for optimizing ship operations and reducing energy costs.