Journal of Transportation Systems Engineering and Information Technology ›› 2023, Vol. 23 ›› Issue (6): 215-226.DOI: 10.16097/j.cnki.1009-6744.2023.06.022

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Comprehensive Optimization Model and Algorithm of Operation Plan for Smart Port Station of Heavy Haul Railway

WU Yi-dia,HE Shi-wei*a, b,ZHOU Hana   

  1. a. School of Traffic and Transportation; b. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
  • Received:2023-07-21 Revised:2023-09-10 Accepted:2023-09-12 Online:2023-12-25 Published:2023-12-23
  • Supported by:
    National Natural Science Foundation of China (62076023);Fundamental Research Funds for the Central Universities of Ministry of Education of China (2022JBQY006);Research Project of China Railway Corporation (P2022X013)。

重载铁路智慧港口站作业计划综合优化模型及算法研究

吴艺迪a,何世伟*a, b,周汉a   

  1. 北京交通大学,a. 交通运输学院;b. 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
  • 作者简介:吴艺迪(1997- ),男,北京人,博士生。
  • 基金资助:
    国家自然科学基金 (62076023);中央高校基本科研业务费专项资金 (2022JBQY006);中国国家铁路集团有限公司科技研究开发计划项目 (P2022X013)。

Abstract: To improve the intelligent level of the port station scheduling, this paper focuses on the operation organization of the port station of heavy haul railway and analyzes the shunting operation scheme of different unloading systems under the mode of leading locomotive shunting operation. The train disintegration plan, unloading plan, shunting operation plan and train combination plan are used as the key parameters to describe the entire operation process of different types of heavy haul trains at the station. Considering the unloading capacity of the port station and the transport efficiency of the empty trains after unloading, this paper develops a hybrid integer linear programming model for the comprehensive optimization of operation plan of the port station of heavy haul railway. The objective function reflects the minimum residence time of the trains. The hybrid algorithm combining micro-evolution with heuristic strategy and adaptive neighborhood search is designed to solve the model. The case study in a port station of a heavy haul railway show that there is no idle waiting time in the equipment cooperative scheduling scheme, and the first 7 departure trains from the train allocation scheme satisfy the maximum combination number of empty trains. By comparing different shunting operation schemes, the mode of leading locomotive shunting operation can reduce 5 switch engines for port station. Compared with Gurobi solver, the proposed algorithm can save 97.32% of the computing time and reduce the gap to the optimal lower bound by 0.06%.

Key words: railway transportation, operation plan, micro-evolution algorithm, smart port station, comprehensive optimization

摘要: 为提升港口站调度智能化水平,本文在研究重载铁路港口站作业组织的基础上,分析本务机担当调机运用模式下不同卸车系统的调车作业方案,以列车分解计划、卸车计划、调车作业计划及列车组合计划为核心刻画不同类型重载列车在站作业全流程。考虑港口站卸车作业能力和卸后空车返程排空效率,以车辆在站停留时间最少为目标函数,构建重载铁路港口站作业计划综合优化的混合整数线性规划模型,采用带有启发式策略的微进化与自适应邻域搜索相结合的混合算法。以某重载铁路港口站为例进行分析,结果表明,得到的设备协同调度方案中未出现空闲等待时间,出发列车配流方案中,前7列均满足最大空车编成辆数;对比不同调车作业方案,本务机担当调机运用模式可为港口站减少5台调车机;所提算法相比Gurobi求解器,在求解时间上节省97.32%,与最优下界值间隔缩小0.06%。

关键词: 铁路运输, 作业计划, 微进化算法, 智慧港口站, 综合优化

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