动车运用所调车作业计划优化  

Optimization of shunting operation plan of electrical multiple unit depots

作　　者：范贤 徐小明 钱程 FAN Xian;XU Xiao-ming;QIAN Cheng(School of Automotive and Transportation Engineering,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]合肥工业大学汽车与交通工程学院,安徽合肥230009

出　　处：《山东科学》2022年第2期96-105,共10页Shandong Science

基　　金：国家自然科学基金(72071059);中国博士后科学基金(2019M662144)。

摘　　要：动车运用所的调车计划编制随着检修任务的增加而变得越来越复杂,调车计划编制的自动化对于增强动车运用所的检修能力具有重要意义。以最小化动车组检修任务完成时的时刻之和为目标,考虑动车运用所的股道占用冲突等约束构建优化模型,设计的贪婪算法结合邻域搜索的启发式算法可以对调车计划编制的自动化问题进行快速求解。最后,设计算例验证本文算法的有效性。研究发现,对于15组动车组规模的5个算例,平均Gap值为0.87%,且有3个算例直接求出了最优解;对于20组动车组规模的5个算例,邻域搜索改进的平均值为1.35%。With increasing maintenance tasks in electric multiple unit(EMU) depots, shunting operation plans are becoming increasingly complex. The automation of shunting plan preparation is crucial for enhancing the maintenance ability of EMU depots. This study aims to minimize the total maintenance time of EMU trains and construct an optimization model that considers the occupancy conflict of the operation tracks in EMU depots. A heuristic algorithm comprising the greedy algorithm combined with neighborhood search is proposed to solve the automation of shunting plan quickly. Finally, a computational study is designed to verify the effectiveness of the proposed algorithm. Results show that for five cases with an EMU size of 15 each, the average Gap value is 0.87% and the optimal solution is directly obtained in three cases. In five cases with an EMU size of 20 each, the average value of the neighborhood search improvement is 1.35%.

关 键 词：动车运用所 动车组检修 调车作业计划 贪婪算法 邻域搜索 

分 类 号：U292.2[交通运输工程—交通运输规划与管理]