客流需求不确定下城市轨道交通线路协同限流鲁棒优化研究

研究了客流需求不确定下城市轨道交通线路协同限流问题。构建了城市轨道交通线路协同限流确定性模型,在此基础上,基于情景分析的鲁棒优化方法,采用具有已知概率的情景集描述客流需求的不确定性,将此模型扩展为含不确定因素的鲁棒优化模型,对每个时段每个车站的最佳进站量进行了求解,达到在保障运营安全的同时使站外的滞留人数最少的目的,并以北京地铁八通线为例对模型进行了验证。通过将确定性模型与鲁棒模型进行对比发现,鲁棒模型能降低限流策略对不确定客流需求的敏感程度,使不同需求情景下的滞留人数保持在可接受的范围内。

Robust optimization of the coordinated passenger inflow controlin a metro line under uncertain passenger demand

A deterministic coordinated passenger inflow control model was formulated. and an extended model was constructed under uncertain passenger demand by introducing a robust optimization approach based on scenario analysis, where the uncertain passenger demand can be represented by several scenario sets with given probabilities.The optimal inbound passenger volume with respect to each station during each equivalent time interval can be obtained to minimize the total number of passengers stranded outside each station.Beijing Metro Batong line was considered to verify the performance of the proposed model. When compared with the deterministic model, the results denote that the robust model can reduce the sensitivity of the control strategy to uncertain passenger demand and maintain the number of stranded passengers in an acceptable range under various demand scenarios.