Multi-objective optimal thrust allocation strategy for automatic berthing of surface ships using adaptive non-dominated sorting genetic algorithm III

The automated berthing of vessels constitutes a high -risk operation. Equipping ships with azimuth and lateral thrusters enhances manoeuvrability, although it poses challenges in achieving optimal thrust allocation (TA) efficiency. This study introduces an improved adaptive non -dominated sorting genetic algorithm III (ANSGAIII) specifically designed to address the TA problem in autonomous ship berthing. The algorithm enhances the objective function by accounting for the nonlinear relationship between actual power consumption and thruster speed, along with considering the treatment of forbidden sectors while maintaining a high level of fidelity. Additionally, the algorithm considers equality constraints, actuator rate and position constraints, and other operational constraints. A modification to the non -dominated sorting method is implemented to improve the processing speed of the optimization algorithm. Significantly, this algorithm surpasses NSGAII, NSGAIII, and CMOEA\D in meeting ship safety and stability requirements while concurrently reducing energy consumption.