Abstract:

This paper investigates the horizontal alignment and station location of the underground urban rail transit considering the fixed starting and ending points and the study area population distributions. A mathematical model was established to optimize the number and location of stations and the horizontal alignment of the rail transit. The model considers the constraints of geographical requirements, station spacing, transfer reservations, and horizontal track alignment design. The objectives are maximizing the attracted passenger flow while minimizing the overall costs which include construction investment, operating expenditure and environmental impact. A hybrid heuristic algorithm based on non- dominated sorting genetic algorithm (NSGA- II) and A* algorithm was designed to solve the model. A case study on Chinese Metro shows that the pareto frontier of the model can be solved by the proposed algorithm, which provides the solution with the minimal overall costs under the different attracted passenger number. In addition, compared with the practical alignment, the horizontal alignment optimized by the proposed model decreases the overall costs of line by about 4.4% without a reduction of attracted passenger flow.

Key words: urban traffic, horizontal alignment design, non- dominated sorting genetic algorithm, station location, overall costs

摘要：

基于已知的线路起终点和研究区域内人口分布情况，研究城市轨道交通地下线平面设计方案。以轨道交通车站的布设数量、位置及线路平面线形为决策变量，考虑实际地理条件、站间距、换乘预留及线路平面设计等约束，建立城市轨道交通地下线平面优化模型，实现客流吸引量最大，以及包括建设投资、运营支出和环境影响在内的线路综合成本最小。设计基于非支配排序遗传算法(NSGA-II)与A*算法的混合启发式算法求解模型。选取国内某城市地铁线路为研究对象，结果表明，算法可求得模型帕累托前沿，提供不同客流吸引量下线路综合成本最低的解决方案。此外，与实际平面设计方案相比，帕累托最优方案能够在不降低客流吸引量情况下减小约 4.4％的线路综合成本。

关键词: 城市交通, 平面设计, 非支配排序遗传算法, 车站选址, 综合成本