城市的快速发展使其愈加依赖于生命线基础设施系统，城市在自然或人为突发事件面前的脆弱性日益凸显，城市面对突发事件后的运行与恢复问题受到广泛关注。冬季极端冰雪天气对城市路网系统带来极大冲击，严重降低路网服务能力。本文基于韧性城市视角，对冰雪天气下城市路网韧性的概念和度量方法进行了分析。以提升路网韧性为目标，建立冰雪天气下路网恢复问题的数学模型，解决极端冰雪天气不确定信息下的城市路网除雪应急物资布局问题及其除雪作业优化问题，并设计了相应的启发式求解算法。最后通过算例验证了模型和算法的有效性，以期为城市冰雪天气应对提供决策支持，提升城市应对极端冰雪天气的韧性。
The winter snow and ice weather brings great impact on the urban road network traffic, which will seriously reduce the overall resilience of city. Because of the limits of emergency budget, the location and allocation of snow removal resources is highly correlated with the safety of urban traffic. Based on the perspective of the Resilient City,according to the historical winter weather data and road network structure in a certain city, how to optimize the layout of snow removal resources before snow weather and the plans of snow removal operations in different weather scenarios are studied, in order to improve the absorbing ability and recovering ability to extreme snow weather of urban road network.First, the average speed is used as the index of road network service capability and the Independent Pathway instead of all common pathway is taken as the evaluation target in the urban road network. Secondly, the whole wave process of road network is divided into two periods:absorbing period and recovering period. Accordingly, the metric resilience of urban road network can be expressed as:Res=((Td-T0)*(MOPnew-MOPmin))/(Tmax-T0)*(MOP0-MOPmin), where T is the time index and MOP is service ability of the road network. Among them,(Td-T0) is the absorption period;(Tmax-T0) is the whole wave process of road network;(MOPnew-MOPmin) is the recovery value;(MOP0-MOPmin) is the damage value. The four indexes are used to define the resilience (Res) of urban road network under snow and ice weather, which is set as the optimization target.A higher numerical value of the Res implies a strong resilience of road network. Thus, the LRP mathematical model is established based on optimization target. Third, the improved tabu search algorithm is designed based on the road classification. Last, the numerical analysis about the problem is made, thus, the following conclusions can be obtained. The resilience can systematically reflect the recovery process and can be set as the optimization target of road recovery under snow and ice weather. It is necessary to put the snow removal resources into the critical roads.The numerical result verifies the reliability of the model and method we processed. The study provides some management measures for road network restoration.
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