地铁网络服务韧性评估与最优恢复策略

交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (5): 198-205.

地铁网络服务韧性评估与最优恢复策略

吕彪^{*1, 2}，管心怡¹，高自强¹

1. 西南交通大学，信息科学与技术学院，成都 611756；2. 四川省列车运行控制技术工程研究中心，成都 611756

收稿日期:2020-12-13 修回日期:2021-02-04 接受日期:2021-02-05 出版日期:2021-10-25 发布日期:2021-10-21
作者简介:吕彪(1980- )，男，重庆荣昌人，讲师，博士。
基金资助:
教育部人文社会科学研究青年基金；中央高校基本科研业务费专项资金

Evaluation and Optimal Recovery Strategy of Metro Network Service Resilience

LV Biao^{*1, 2} , GUAN Xin-yi¹ , GAO Zi-qiang¹

1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China； 2. Sichuan Provincial Engineering Research Center of Train Operation Control, Chengdu 611756, China

Received:2020-12-13 Revised:2021-02-04 Accepted:2021-02-05 Online:2021-10-25 Published:2021-10-21
Supported by:
Ministry of Education Humanities and Social Sciences Research Youth Fund Project；Fundamental Research Funds for the Central Universitie

摘要/Abstract

摘要： 针对已有基于拓扑效率的地铁网络韧性指标无法反映地铁运营实际的不足，构建考虑线路流量影响的路网服务效率指标和基于服务效率的路网服务韧性指标，以及基于路网服务效率的节点重要度指标；提出以路网服务韧性最大化为目标的优化模型，并基于遗传算法求解模型获得最优恢复策略。算例结果表明：分别以服务效率和拓扑效率作为路网性能指标，获得的失效节点恢复次序明显不同；蓄意攻击下，最优恢复策略获得的路网服务韧性分别比基于重要度的优先恢复策略、基于节点度的优先恢复策略和随机恢复策略高16.76%、72.11%和86.21%。上述结果表明，必须根据地铁运营实际合理选择路网性能指标和恢复策略，否则可能得到次优甚至明显偏离实际的方案，无法实现预期目标。

关键词: 交通工程, 服务韧性, 最优恢复, 地铁网络, 遗传算法, 服务效率, 节点重要度

Abstract: Since the existing network resilience indexes based on topological efficiency cannot reflect the actual metro operation situations, a novel index of metro network service efficiency considering the influence of line flows, an index of metro network service resilience based on service efficiency, and an index of node importance based on metro network service efficiency were constructed. An optimization model was proposed to maximize the metro network service resilience, and then an optimal recovery strategy was obtained by solving the model using a genetic algorithm. The results show that the recovery orders of failure nodes are different by taking service efficiency and topological efficiency as metro network performance index respectively. Under the deliberate attack, the network service resilience obtained by the optimal recovery strategy is 16.76%, 72.11%, and 86.21% higher than the priority recovery strategy based on node importance, the priority recovery strategy based on node degree, and the random recovery strategy, respectively. The above results indicate that the network performance indexes and the recovery strategies should be selected reasonably according to the actual metro operation situations. Otherwise, the suboptimal or even worse schemes which significantly deviate from the actual situations may be obtained, and thus the expected goals cannot be achieved.

Key words: traffic engineering, service resilience, optimal recovery, metro network, genetic algorithm, service efficiency, node importance

中图分类号:

U491

吕彪, 管心怡, 高自强. 地铁网络服务韧性评估与最优恢复策略[J]. 交通运输系统工程与信息, 2021, 21(5): 198-205.

LV Biao , GUAN Xin-yi, GAO Zi-qiang. Evaluation and Optimal Recovery Strategy of Metro Network Service Resilience[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 198-205.

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