基于弹复性的交通网络应急恢复阶段策略优化

重大灾难的灾后恢复一般分为应急恢复阶段和全面恢复阶段,前者面临时间、资金、资源有限等多重困难.传统交通网络灾后恢复研究缺乏结合应急恢复阶段特点的针对性研究.为此,提出一种基于弹复性的交通网络应急恢复阶段策略优化模型.首先,提出两个弹复性度量指标,分别从网络性能恢复速度和累计损失两方面度量弹复性.然后,针对应急恢复阶段,同时考虑上层系统弹复性和下层用户行为的交互,建立交通网络恢复策略双层优化模型.结合并行机调度问题算法和用户均衡配流问题算法,设计一种特殊的交互式双层算法.最后,通过案例验证了模型有效性,表明模型和算法能根据资源、资金、恢复目标、决策者偏好等因素,有效求解大规模交通网络应急恢复阶段的最优恢复策略.

Resilience-based recovery strategy optimization in emergency recovery phase for transportation networks

Recovery from major disasters is generally divided into an emergency recovery phase and a comprehensive recovery phase. The former faces multiple difficulties such as limits of time, funds and resources. The traditional research of post-disaster recovery of transportation networks lacks targeted research that combines the characteristics of the emergency recovery phase. To address these problems, a resilience-based optimization model of the recovery strategy in the emergency recovery phase for transportation networks is proposed. Firstly, two resilience metrics are proposed to measure resilience from both the recovery rapidity and the cumulative loss of network performance. Then, considering the interaction between system resilience at the upper level and user behavior at the lower level, a bi-level programming model for the transportation network recovery strategy in the emergency recovery phase is established. A special interactive bi-level algorithm is designed by combining the algorithm for the parallel machine scheduling problem and the algorithm for the user equilibrium problem. Finally, the validity of the proposed model is verified by a case study. The results indicate that the proposed model and algorithm can effectively determine the optimal recovery strategy in the emergency recovery phase for large-scale transportation networks with constraints of resources, funds, recovery goals, decision maker preference, etc.