摘要
以共堆场海铁联运为主要运输方式,引入时间窗约束下的车船直取与船铁直取2种模式;同时,将天气等环境不确定因素以及集卡与场桥设备切换所需时间纳入考量。以最小化集卡总行驶时间为优化目标,通过有向图对堆场道路网络进行抽象,构建相应的数学模型。采用粒子群算法对多模式切换情景下的共堆场海铁联运路径优化问题进行求解。实验结果表明,该模型结合粒子群优化方法,能显著提升集卡运输效率,为作业路径优化及港口作业效能提升提供决策支持。
s the yard road network into a directed graph and establishes a corresponding mathematical model.The particle swarm optimization(PSO)algorithm is then applied to solve the path optimization problem under multi-modal transition scenarios.Experimental results demonstrate that the proposed model,when combined with the PSO algorithm,can significantly enhance truck transportation efficiency and provide strong decision support for optimizing operation routes and improving port operational performance.
作者
叶清
钟朝文
李尤
葛含章
孙颖
YE Qing;ZHONG Chaowen;LI You;GE Hanzhang;SUN Ying(Guangxi Yanhai Railway Company Limited,Nanning 530003,China;School of Civil Engineering,Central South University,Changsha 410075,China)
出处
《交通工程》
2025年第12期29-37,共9页
Journal of Transportation Engineering
关键词
集卡路径优化
海铁联运
直取模式
行驶时间
粒子群算法
truck route optimization
sea-rail intermodal transportation
direct loading mode
driving time
particle swarm optimization
