带时间窗的中心站多车程集卡调度优化研究

doi:10.16097/j.cnki.1009-6744.2024.01.027

交通运输系统工程与信息 ›› 2024, Vol. 24 ›› Issue (1): 272-281.DOI: 10.16097/j.cnki.1009-6744.2024.01.027

带时间窗的中心站多车程集卡调度优化研究

李琦，魏玉光^*

北京交通大学，交通运输学院，北京 100044

收稿日期:2023-09-18 修回日期:2023-12-04 接受日期:2023-12-06 出版日期:2024-02-25 发布日期:2024-02-14
作者简介:李琦(1999- )，男，河北秦皇岛人，博士生
基金资助:
中央高校基本科研业务费专项资金 (2022JBQY006)

Multi-trip Truck Scheduling Optimization of Central Station with Time Window

LI Qi, WEI Yuguang^*

School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China

Received:2023-09-18 Revised:2023-12-04 Accepted:2023-12-06 Online:2024-02-25 Published:2024-02-14
Supported by:
Fundamental Research Funds for the Central Universities of Ministry of Education of China (2022JBQY006)

摘要/Abstract

摘要： 为解决铁路集装箱中心站与周边货源地间的公铁联运多车程集卡集疏调度问题，将货源地的每一集装箱集疏需求视为一个任务节点，以集卡调度总成本最小为目标，综合考虑集卡容量和集装箱集疏时间窗等约束，构建允许同一集卡重复利用的多车程集卡调度优化模型，并设计改进的遗传算法求解该模型。为均衡集卡工作时间，以调度模型确定的最佳集卡数量和车程集合为输入，进一步构建以集卡作业时间之差最小为目标的集卡车程分配模型，并借助Gurobi精确求解每一集卡的最佳车程任务。以郑州铁路集装箱中心站为例进行实验验证，结果表明：本文所提方法能有效解决公铁联运集装箱在集疏环节的集卡调度问题；相较于单车程模式，多车程模式下集卡调度成本平均减少了60.31%；车程分配优化可以将集卡作业时间最大差值减少14.3%以上，提高了集卡作业时间的均衡性。

关键词: 综合运输, 集卡调度方案, 改进遗传算法, 多车程, 集装箱

Abstract: To address the multi-trip intermodal truck scheduling challenges between the railway container center station and the surrounding supply locations, this study defines each container's arrival and dispatch demands at the supply locations as individual task nodes. The objective is to minimize the total cost of truck scheduling while considering constraints such as truck capacity and time windows for container arrival and dispatch. An optimization model is proposed for multi-trip truck scheduling, which allows trucks to be used for several trips. This model is solved by an improved genetic algorithm. For better truck scheduling, this study uses the best number of trucks determined by the model and their respective trips as a starting point. Then, a model is developed to assign truck trips, which aims to minimize differences in the operation times. The Gurobi method is used to find the best tasks for each truck with high accuracy. In testing at the Zhengzhou Railway Container Center Station, the proposed method effectively resolved truck scheduling problems in moving containers during the supply and dispatch process. By using the multi-trip approach instead of single-trip transport, the average truck scheduling cost is saved by 60.31%. Additionally, the optimization of trip allocation can save the maximum difference in truck operation time by over 14.3% and improve the overall balance in truck operation time.

Key words: integrated transportation, transportation dispatching plan, improved genetic algorithm, multiple trips; container

中图分类号:

U169.7

李琦, 魏玉光. 带时间窗的中心站多车程集卡调度优化研究[J]. 交通运输系统工程与信息, 2024, 24(1): 272-281.

LI Qi, WEI Yuguang. Multi-trip Truck Scheduling Optimization of Central Station with Time Window[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(1): 272-281.

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http://www.tseit.org.cn/CN/Y2024/V24/I1/272

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带时间窗的中心站多车程集卡调度优化研究

Multi-trip Truck Scheduling Optimization of Central Station with Time Window

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