为实时响应海上环境变化并调整搜索策略，优化全局最优航线，本文探讨基于遗传算法的海上运输最优航线优化方法。通过构建海上运输船舶燃油消耗模型，精确计算船舶主机与副机的油耗，进而建立以最小化船舶油耗和海上运输综合成本为目标函数的优化模型。利用遗传算法根据海上环境的动态变化实时调整搜索策略，求解该模型，从而获得最小化船舶油耗与综合成本的最优航线。实验结果表明：该方法在模型求解方面表现优异，最大间距指标约为25，显著低于间距指标阈值（30）；同时，该方法能有效优化海上运输航线，显著降低船舶油耗（从1086.7 t降至924.5 t）和综合成本（从354.2万元降至321.7万元）。
In order to respond to changes in the maritime environment in real time and adjust search strategies to optimize the global optimal route, this study explores a genetic algorithm based method for optimizing the optimal route of maritime transportation. By constructing a fuel consumption model for maritime transport vessels, the fuel consumption of the main and auxiliary engines of the vessel is accurately calculated, and an optimization model is established with the objective function of minimizing the fuel consumption of the vessel and the comprehensive cost of maritime transport. Using genetic algorithms to adjust search strategies in real-time based on the dynamic changes in the marine environment, the model is solved to obtain the optimal route that minimizes ship fuel consumption and overall costs. The experimental results show that this method performs well in model solving, with a maximum spacing index of about 25, significantly lower than the spacing index threshold (30); Meanwhile, this method can effectively optimize maritime transportation routes, significantly reducing ship fuel consumption (from 1086.7 t to 924.5 t) and overall costs (from 3.542 million yuan to 3.217 million yuan).
2025,47(19): 185-189 收稿日期：2025-4-15
DOI：10.3404/j.issn.1672-7649.2025.19.030
分类号：U692; U692.33
基金项目：2023年度广西重点研发计划项目（2023AB30024）；2023年度广西重点研发计划项目（2023AB08033）；2023年度广西重点研发计划项目（2023AB11006）；2024年度广西科技基地和人才专项项目（2024AC35003）
作者简介：黄勇(1981-),男,教授/高级工程师,研究方向为交通规划
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