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摘要: 针对大型公共场所突发事件提出了运用公共交通进行紧急疏散的集成优化模型。模型将紧急疏散问题抽象为行人交通流和公共交通网络的双层优化网络, 第1层引导撤离人员从事发地点(建筑物等) 到达指定的乘车点(公交站等), 第2层优化公交车从场站出发, 途经各乘车点, 最后运输撤离人员到达安全地点。利用基于禁忌搜索的两阶段启发式算法对模型进行求解和验证。验证结果表明: 在一个有328人需要疏散的网络中, 共使用8辆公交车完成疏散。目标函数中每一项权重的变化对模型输出结果基本没有影响, 模型具有很强的鲁棒性。对比CPLEX优化软件, 启发式算法能够在1h内求解出近似最优解, 并且近似最优解与最优解的误差小于15%。模型充分考虑了撤离人员分配与公交路径优化之间的交互影响, 实现了在紧急疏散时行人交通流与公共交通网络的组织最优。Abstract: Aiming at emergent event in large-scale public, an integrated optimization model of emergency evacuation was developed based on public transit.In the model, the problem of emergency evacuation was summarized as a two-level optimization network including pedestrian traffic flow and public transit network.The first-level framework guided evacuees from accident sites (e.g.buildings) to designated pick-up points (e.g.bus stops).The second-level framework properly dispatched and routed a fleet of buses at different transit depots to the pick-up points, and transported evacuees to safe places finally.Integrated optimization model was tested and verified by using a two-stage heuristic algorithm based on tabu search.Verification result indicates that 8 buses are used for the evacuation of all 328 people in the network.The output result of integrated optimization model is not sensitive to the change of weight assignment of objective function, so the model has strong robustness.Comparing with the optimization software of CPLEX, heuristic algorithm can get near optimum solution in 1 h, and the error between near optimum solution and optimal solution is less than 15%.The interactions betweenevacuees distribution and bus route optimization are fully considered in the model.The pedestrian traffic flow and the public transit network during evacuation process are concurrently optimized.
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Key words:
- public transit /
- emergent event /
- emergency evacuation /
- pedestrian /
- integrated optimization model /
- tabu search
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表 1 节点和车辆信息
Table 1. Node and vehicle information
表 2 每个建筑物中需撤离人数
Table 2. Evacuee number at each building
表 3 每个乘车点的容量
Table 3. Capacity of each pick-up point
表 4 建筑物到乘车点的距离
Table 4. Distances from buildings to pick-up points
表 5 车辆网络的距离矩阵
Table 5. Distance matrix of vehicular network
表 6 分配结果
Table 6. Assignment result
表 7 每辆公交车的疏散路径和总疏散量
Table 7. Routing plan and total evacuee number of each bus
表 8 权重对总疏散量的影响
Table 8. Effect of objective weights on total evacuee numbers
表 9 不同情景的计算结果
Table 9. Calculation results of different scenarios
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