考虑股道运用的重载卸车站作业计划优化研究  

Optimization study on operation plan of heavy-haul unloading station considering use of track

作　　者：周汉 何世伟[1] 吴艺迪 张哲铭[1] ZHOU Han;HE Shiwei;WU Yidi;ZHANG Zheming(Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室,北京100044

出　　处：《铁道科学与工程学报》2024年第4期1402-1411,共10页Journal of Railway Science and Engineering

基　　金：中央高校基本科研业务费资助项目(2022JBQY006);国家自然科学基金资助项目(62076023);中国国家铁路集团有限公司科技研究开发计划课题(P2022X013)。

摘　　要：重载卸车站是重载运输的重要组成部分,实现车站作业计划自动化编制对于加速列车周转时间、提高重载运输生产效率具有重要意义。重载卸车站由于列车在站作业种类多,车站作业计划编制复杂。为实现计算机自动化编制高效智能的车站作业计划,在分析重载列车在车站作业流程的基础上,将重载列车在站技术作业过程转化为对卸车站内到达线股道、存车线股道、卸煤线股道、清煤线股道、组合线股道的5次占用问题,构建考虑股道运用的重载卸车站作业计划模型。考虑到模型属于NP-hard问题,设计微进化算法进行求解,并在微进化算法基础上引入大规模邻域搜索算法中的损坏和修复思想对算子操作进行改进。以朔黄铁路终端黄骅港站某夜间到达的15列重载列车为实际案例,对提出的模型和算法进行验证。研究结果表明:微进化算法所采用的优势基因结构机制能快速有效解决重载卸车站作业计划编制问题,相较于GUROBI求解器,其求解质量在95%以上且求解时间缩短48.16%,同时相较于遗传算法其求解质量提升5.38%且求解时间缩短27.49%。微进化算法得出的优化计划相较于人工编制计划,重载列车在站总时长缩短了389 min,提升了重载卸车站作业计划质量。研究结果能缩短重载列车在站作业时间,加速重载列车在站中转过程,为计算机自动编制车站作业计划提供智能决策。Heavy-haul unloading stations were an important part of heavy-haul transportation,and it was important to automate station operation planning to accelerate train turnaround time and improve heavy-haul transportation production efficiency.To automate the preparation of efficient and intelligent station operation plan,the station operation plan was complicated due to the many types of train operations at the station.Based on the analysis of heavy-hual train operation process in the station,the technical operation process of heavy-haul trains in the station was transformed into the five occupation problems of arrival line track,storage line track,coal unloading line track,coal cleaning line track,and combination line track in the unloading station,A heavy-haul unloading station operation plan model was constructed considering the use of track.Considering that the model belongs to the NP-hard problem,a Micro-evolutionary algorithm was designed to solve it.The operator operation is improved by introducing the idea of damage and repair in the large-scale domain search algorithm on the basis of the micro-evolutionary algorithm.The proposed model and algorithm were verified by taking 15 heavy trains arriving at a certain night at Huanghua port station of Shuohuang Railway Terminal as a practical case.The results show that the advantageous gene structure mechanism adopted by the Micro-evolution algorithm can quickly and effectively solve the operation planning problem of the heavy-hual unloading station,Its solution quality is more than 95%and the solution time is shortened by 48.16%compared with the GUROBI solver.Its solution quality is improved by 5.38%and the solution time is shortened by 27.49%compared with the genetic algorithm.The optimized plan derived from the Micro-evolutionary algorithm shortens the total time of heavy trains at stations by 389 minutes compared with the manual plan,and improves the quality of the operation plan at heavy-haul unloading stations.The present results can shorten the operating time o

关 键 词：重载运输 车站作业计划 股道运用 微进化算法 黄骅港站 

分 类 号：U292.12[交通运输工程—交通运输规划与管理]