不同需求日高铁列车开行方案协同优化方法

The collaborative optimization of multi-day line plannings for high-speed railway

不同需求日的出行需求在结构和总量上都存在差异,不仅需要提供与各需求日相匹配的运输能力,而且不同需求日的列车开行方案应有很大相似性,使高铁运输组织能平稳过渡。为权衡铁路运营成本和运输组织衔接,在考虑高铁运输组织平稳过渡前提下,谋求铁路运输成本和旅客出行费用最小,对不同需求日列车开行方案进行协同优化。由各需求日各OD对需求生成最大包络需求,以最大包络需求列车开行方案为备选列车集,产生各个需求日的列车开行方案。建立不同需求日开行方案协同优化双层规划模型,设计求解模型的遗传算法。算例分析表明,在公共列车集比例限制下,协同优化产生的开行方案具有较好评价指标,算法收敛性较好,体现了模型和算法的有效性。

The differences of passenger demand among multi-day in passenger flow volume and time-varying structure requires that line plannings among multi-day can provide the corresponding capacity. Meanwhile, line plannings among multi-day need to have a lot of similarities to ensure the transport organizations can transit smoothly. In order to coordinate the railway operating costs and transport organizations cohesion, the railway operation costs and travel expenses of passengers are minimized on the premise of a smooth transition of high-speed rail transport organizations of multi-day. The collaborative optimization method of multi-day line plannings is carried out. In this method, each OD needs to generate the maximum demand for each day and solve the maximum demand line planning as a candidate train set, then the line planning for each day is preferably generated. The collaborative optimization bi-level programming model was established based on the multi-day and design the genetic algorithm to solve the model. The numerical example shows that under the constraint of the proportion of public train set, the line plannings which are produced by collaborative optimization method have good evaluation indexes, and the convergence of the algorithm shows the validity of the model and the algorithm.