路径规划, 气象航线, 遗传算法, 蚁群算法

To address the limitations of traditional heuristic algorithms in solving the ship ocean weather routing problem, namely slow convergence, susceptibility to local optima, and high dependence on parameter settings,an improved route planning framework is constructed based on intelligent optimization algorithms. By integrating the advantages of genetic algorithm, ant colony algorithm and simulated annealing algorithm, a reversal mutation and pheromone fusion mutation strategy is proposed, and a horizontal dynamic adjustment mechanism is designed based on fitness and a vertical dynamic adjustment mechanism based on simulated annealing for genetic probabilities. These strategies enhance the global optimization capability and convergence efficiency of the algorithm. Comparative simulation experiments show that, compared to traditional algorithms, the proposed fusion algorithm shortens the path length by 11. 7% ~ 36. 7% and reduces the navigation time by 12. 2%~37. 4% , verifying its optimization performance in complex meteorological environments.

path planning, meteorological route, genetic algorithm, ant colony algorithm