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针对单条城市轨道线路,充分考虑乘客出发时刻选择行为,以列车始发站发车时刻为决策变量,构建城市轨道列车时刻表双层优化模型。上层以运营单位及乘客综合费用最小为目标,以列车发车间隔、首末班车时刻、运输供给水平等为约束,建立列车时刻表优化模型;下层以列车容量为强约束条件,在充分考虑个体乘客选择行为相互作用的基础上,建立考虑乘客出发时刻选择的均衡配流模型,从而有效反映列车开行方案对乘客出发时刻选择的影响。根据模型特点,设计遗传算法和MSA算法对上、下层模型求解。通过算例验证模型及算法的有效性,并对乘客期望到达时刻进行灵敏度分析,结果表明:与既有优化方法相比,本文模型能够更为有效地降低乘客出行费用及系统总费用;随乘客期望到达时刻离散化程度的提高,列车超载与低载客现象减少,综合费用、乘客出行总费用及运营费用将下降。
Aiming at the single track line in a city, the selection behavior of passenger departure time is fully considered, and the departure time of train originating station is taken as the decision variable to construct a double-layer optimization model of train schedule. The upper level of the operating unit and passenger minimum cost as the goal, the train departure interval, the first bus time, transportation supply level as the constraint, the establishment of train timetable optimization model; the lower the train capacity is strong constraints, taking full account of individual passenger choice Based on the interaction between passengers and passengers, an equilibrium distribution model considering the passenger departure time is established to effectively reflect the influence of train operation on passenger departure time selection. According to the characteristics of the model, genetic algorithm and MSA algorithm are designed to solve the upper and lower model. The effectiveness of the model and the algorithm is verified through an example, and the sensitivity analysis of passengers’ expected arrival time is carried out. The results show that compared with the existing optimization methods, the proposed model can reduce the travel cost and the total system cost more effectively. Expected to reach the discretion of the time to improve the train overloading and low passenger reduction, the overall cost of passenger travel expenses and operating costs will decline.