中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2025, Vol. 44 ›› Issue (6): 97-107.DOI: 10.3969/j.issn.1674-0696.2025.06.10

• 交通+大数据人工智能 • 上一篇    

基于改进免疫遗传算法的海铁转运设备作业调度优化研究

黄鹏飞1,2,谈方娇1,王浩1,江瑀越1,蔡锦汾1   

  1. (1. 集美大学 航海学院,福建 厦门 361021; 2. 集美大学 海上交通运行智能控制与仿真技术国家地方联合工程研究中心,福建 厦门 361021)
  • 收稿日期:2024-07-17 修回日期:2024-10-30 发布日期:2025-06-30
  • 作者简介:黄鹏飞(1975—),男,福建厦门人,副教授,主要从事交通运输工程方面的研究。E-mail:199861000046@jmu.edu.cn
  • 基金资助:
    福建省自然科学基金资助项目(2021J01820)

Scheduling Optimization for Sea-Rail Transport Equipment Based on Improved Immune Genetic Algorithm

HUANG Pengfei1,2, TAN Fangjiao1, WANG Hao1, JIANG Yuyue1, CAI Jinfen1   

  1. (1. Navigation College, Jimei University, Xiamen 361021, Fujian, China; 2. National Local Joint Engineering Research Center for Ship-Aided Navigation Technology, Jimei University, Xiamen 361021, Fujian, China)
  • Received:2024-07-17 Revised:2024-10-30 Published:2025-06-30

摘要: 集装箱转运作为连接海运与铁路运输的关键环节,其效率直接影响到整个物流链的顺畅运行。缩短集装箱在港停留时间、 优化设备作业顺序以及提升转运效率对于实现高效的海铁联运至关重要。但现有研究往往忽视了对集装箱完整转运流程及设备空载时间因素的考虑。鉴于此,针对从船舶卸载至堆场再转至铁路线的全过程,构建了以最小化总作业完成时间为目标函数的数学模型,旨在解决实际存在的连续作业约束、 空载等待时间和具体操作位置等问题;通过采用改进后的免疫遗传算法(特别是引入克隆抗体选择机制和自适应参数调整策略)来求解该问题;经过一系列优化对比证明了该方法能更有效地找到最优解或近似最优解,即最短的总作业完成时间及其对应的设备调度方案。研究成果不仅有助于显著减少港口内集装箱的处理周期,还能促进节能减排。

关键词: 交通运输工程;海铁转运;调度优化;改进免疫遗传算法

Abstract: Container transshipment, as a critical link connecting maritime and railway transportation, whose efficiency directly influences the smooth operation of the whole logistics chain. Shortening container dwell time at ports, optimizing equipment operation sequences and improving transshipment efficiency are essential for achieving efficient sea-rail intermodal transportation. However, the existing studies often overlook the consideration of the complete container transshipment process and the impact of equipment idle time. In response, aiming at the whole process from ship unloading to storage yard and then to railway line, a mathematical model was constructed with the objective function of minimizing the total operation completion time, to address practical issues such as continuous operation constraints, no-load waiting time and specific operation position. The improved immune genetic algorithm (especially the clonal antibody selection mechanism and adaptive parameter adjustment strategy) was used to solve the problem. After a series of optimization and comparison, it is demonstrated that the proposed method can more effectively find the optimal or near-optimal solutions, achieving the shortest total operational completion time and the corresponding equipment scheduling plans. The research results not only help to significantly reduce the processing cycle of containers in ports, but also promote energy conservation and emission reduction.

Key words: traffic and transportation engineering; sea-rail transfer; scheduling optimization; improved immune genetic algorithm

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