为提高物流运输的安全性，实现更加智能化港口运营管理，提出基于鱼群算法的物流运输船舶港口避撞路径跟踪控制。将最短避撞路径作为避撞路径跟踪控制目标函数，在鱼群算法中引入加权平均视觉范围和自适应拥挤度因子，通过鱼群的觅食、聚群和追尾行为寻找物流运输船舶港口的最短避撞路径，作为最终的避撞路径跟踪控制结果。实验结果表明，该方法能够根据实时障碍物信息动态调整路径，为船舶港口避撞路径跟踪控制提供准确可靠的数据支持。
In order to improve the safety of logistics transportation and realize more intelligent port operation and management, the port collision avoidance path tracking control of logistics transport ships based on fish swarm algorithm is proposed. Taking the shortest collision avoidance path as the objective function of the collision avoidance path tracking control, the weighted average visual range and adaptive crowding factor are introduced into the fish swarm algorithm, and the shortest collision avoidance path of the port of the logistics transport ship is found through the foraging, clustering and rear-end behaviors of the fish swarm, as the final collision avoidance path tracking control result. The experimental results show that the proposed method can dynamically adjust the path according to the real-time obstacle information, and provide accurate and reliable data support for ship port collision avoidance path tracking control.
2023,45(24): 208-211 收稿日期：2023-10-13
DOI：10.3404/j.issn.1672-7649.2023.24.040
分类号：TP319
基金项目：江苏省教育科学“十四五”规划课题（D/2021/03/41）
作者简介：王鹏(1982-),男,博士研究生,副教授,研究方向为物流工程及国际贸易
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