摘要
对复杂轨道交通多目标调度效率建模分析,能够降低企业运营成本。多目标调度中,难以及时获取拥塞路段信息,路径选取易出现突发性冲突,需要对调度效率模型进行研究。传统方法考虑不同交通站点之间的客流需求下构建多目标调度模型,调度方法使得平均满载率显著下降,但路径选取出现突发性冲突,导致轨道交通调度效率低。提出一种基于信息整合的复杂轨道交通多目标调度效率数学建模方法。以信息融合理论为依据将复杂轨道交通历史车辆运行数据与客流数据进行相关性整合,及时获取拥塞路段信息;根据数据层与特征层数据的融合结果获得实时发车间隔决策;以乘客候车等待时间最短和发车次数最少为优化目标,构建轨道交通多目标调度效率数学模型,并对细菌觅食优化算法求解该数学模型过程分析。实验结果表明,所提方法提高了多目标调度效率和通行能力。
To model and analyze multi -objective scheduling efficiency of complex rail traffic can reduce the op- erating cost of enterprise. But the traditional method has the sudden conflict of route selection, resulting in low effi- ciency of rail traffic scheduling. In this paper, we present a method for mathematical modeling of multi - objective scheduling efficiency in complex rail traffic based on information integration. On the basis of information fusion, the historical vehicle running data and passenger data in complex rail traffic were integrated to get information of conges- tion road in time. According to the fusion result of data level and feature level, we obtained real - time departure interval decision. Taking the shortest waiting time and the minimum number of departures as the optimization object, the mathematical model of multi - objective scheduling efficiency of rail traffic was built and bacterial foraging optimi- zation algorithm was solved. Simulation result show that the proposed method improves the efficiency of multi - objec- tive scheduling and traffic capacity.
作者
李自强
LI Zi - qiang(College of Science,Ningxia Medical University,Yinchuan,Ningxia,750004,Chin)
出处
《计算机仿真》
北大核心
2018年第8期119-122,共4页
Computer Simulation
关键词
复杂轨道交通
多目标调度效率
信息融合
细菌觅食优化算法
Complex rail traffic
Multi - objective scheduling efficiency
Information fusion
Bacterial foragingoptimization algorithm
