统筹多线路乘务调度,提升城市地铁运营效率与应急响应能力
Unified Crew Planning and Replanning Optimization in Multi-Line Metro Systems Considering Workforce Heterogeneity
- 构建分层时空网络模型,统一建模跨线路乘务员作业空间
- 实测数据表明,方案成本更低、任务完成率更高,尤其在突发事件中优势显著
- 适合关注智能交通系统优化与多线协同调度的研究者与从业者
地铁乘务规划是智慧城市建设的关键环节,直接影响公共交通的运行效率与服务可靠性。随着地铁网络快速扩展,多线路协同调度与突发情况下的快速重规划已成为实现大规模无缝运营的必要条件。然而,现有研究多集中于单一线路,缺乏对跨线路协调与应急重规划的关注。本文提出一种考虑乘务员异质性的多线路乘务规划与重规划统一优化框架。具体地,构建分层时空网络模型以表征统一的乘务员行动空间,并推导出计算高效的约束与公式,以处理乘务员的异质资质与偏好。基于该网络模型,开发了列生成与最短路径调整相结合的求解算法。利用上海与北京地铁的真实数据进行实验,结果表明,所提方法在成本降低与任务完成率方面均优于基准启发式算法,通过引入跨线路协同,在突发事件中对紧急任务的处理效率显著提升。本工作凸显了全局优化与跨线路协同在多线路地铁系统运营中的关键作用,为智慧城市建设中公共交通的高效可靠运行提供了新思路。
原文摘要 · Abstract (English)
Metro crew planning is a key component of smart city development as it directly impacts the operational efficiency and service reliability of public transportation. With the rapid expansion of metro networks, effective multi-line scheduling and emergency management have become essential for large-scale seamless operations. However, current research focuses primarily on individual metro lines,with insufficient attention on cross-line coordination and rapid replanning during disruptions. Here, a unified optimization framework is presented for multi-line metro crew planning and replanning with heterogeneous workforce. Specifically, a hierarchical time-space network model is proposed to represent the unified crew action space, and computationally efficient constraints and formulations are derived for the crew's heterogeneous qualifications and preferences. Solution algorithms based on column generation and shortest path adjustment are further developed, utilizing the proposed network model. Experiments with real data from Shanghai and Beijing Metro demonstrate that the proposed methods outperform benchmark heuristics in both cost reduction and task completion,and achieve notable efficiency gains by incorporating cross-line operations, particularly for urgent tasks during disruptions. This work highlights the role of global optimization and cross-line coordination in multi-line metro system operations, providing insights into the efficient and reliable functioning of public transportation in smart cities.
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