Ship route optimization is a complex multivariable multi-objective problem. To solve this problem, a feasible ship navigation optimization method is proposed, using the waypoints of the route as decision variables, the non navigable area and speed as constraints, and the travel time and fuel consumption as evaluation functions for the quality of the route. A multi-objective optimization model for travel time and fuel consumption under the influence of wind, waves, and currents is established. Then, an improved genetic algorithm with cross mutation operator adaptive evolution is designed to improve the convergence speed of the algorithm. Finally, simulation experiments were conducted on this method and compared with the data of the large circle route. The results indicate that the route planned by this method can successfully reduce flight hours and energy consumption.
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