摘要
针对港口堆场与内陆腹地客户之间的空重集装箱运输问题,本文结合甩挂运输的特点将客户的进出港需求拆分为相互关联的空箱和重箱任务,实现单个决策期内运输系统中集装箱的状态转换与回收工作。状态转换受集装箱货物装卸时间影响,因此需要合理调度牵引车路线,以满足前置任务约束。针对此类问题的特点,本文建立了空重箱运输任务整合的整数规划模型,并设计了基于集群选择的改进蚁群算法进行求解。最后,通过不同规模的仿真算例与现有数学模型及优化算法对比结果可知,本文所提出的改进蚁群算法在此类问题的最优解搜索中具有良好的稳定性和求解效率。
This paper investigates the full and empty container transportation problem in a local area near a terminal. Each inbound and outbound demand can be split an interdependent empty container transport task and a full container transportation task. Therefore, the container could complete Full-Empty state transition and empty container reposition. The state transition time are affected by loading/unloading time, it need reasonable scheduling the tractor fleet, to avoid the two-stage task start time earlier than first-stage finish time, namely pre-task restraint. An integer programming model based on pre-task constraint is built and an Ant Colony Optimization algorithm with Cluster Select(CSACO) is designed. The validity of the model is verified by an example.
作者
徐世达
何雯晴
靳志宏
XU Shi-da;HE Wen-qing;JIN Zhi-hong(College of Transportation Engineering,Dalian Maritime University,Dalian 116026,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2022年第12期55-61,共7页
Operations Research and Management Science
基金
国家自然科学基金面上项目(71572023)
欧盟H2020项目(MSCA-RISE-777742-56)
大连市领军人才项目(2018-573)
辽宁省教育厅高等学校基本科研项目(LJKR0020)。
关键词
整数规划
空重箱转换
前置约束
甩挂运输
蚁群算法
integer programming
full-empty state transition
pre-task restraint
drop and pull transport
ACO
