基于客流时空分布特性的南宁轨道交通1号线列车运行图交路优化

Optimization of Nanning Rail Transit Line 1 Train Diagram Routing Based on Passenger Flow Spatiotemporal Distribution Characteristics

优化调整列车运行图交路,对于节约运行成本、提升服务质量和运营效率具有重要意义。提出了一种基于模拟退火算法思想的粒子群优化算法用于优化调整列车运行图交路。以乘客出行等待时间最小化为目标函数,构建了列车运行图交路优化模型;设计了基于模拟退火算法思想的粒子群优化算法,用于求解变量全局最优解;以南宁轨道交通1号线为例,对列车时刻表的发车时间、发车间隔等要素进行了优化,并分析了优化后的列车运能和运量的匹配性。结合实例发现,提出的模型与算法能够较好地解决列车运能和运量问题,提高了乘客乘车舒适度。

Optimizing and adjusting train diagram routing is of great significance for saving operation cost, improving ser-vices quality and operating efficiency. A PSO(particle swarm optimization) algorithm based on SA(simulated annealing) algorithm is proposed to optimize and to adjust train diagram. Taking the minimization of passenger waiting time as the objective function, an optimization model of train diagram routing is constructed. A PSO algorithm based on SA algorithm is designed to get the global optimal solution of variables. Taking Nanning Rail Transit Line 1 as an example, the departure time, departure interval and other elements of the train timetable are optimized, and the compatibility between the optimized train capacity and the traffic volume is analyzed. It is found through practical case that the proposed model and algorithm can tackle the issues of train capacity and traffic volume well, improving the passenger ride comfort.