The solution of traffic flow organisation optimisation model based on adaptive genetic algorithm

被引:0
|
作者
Zhang, Ji [1 ]
Lv, Hongxia [1 ]
Deng, Boer [1 ]
Wang, Wenxian [2 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu 610031, Peoples R China
[2] Wuyi Univ, Sch Railway Tracks & Transportat, Jiangmen 529020, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
car flow organisation in loading area; vehicle hour consumption; optimisation model; spatial search strategy; adaptive genetic algorithm;
D O I
10.1504/IJHVS.2022.128917
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In order to reduce the workload of the stations along the way, the train flow in the loading area is rationally organised. By designing a vehicle flow organisation method that increases the turnover speed of trucks, it helps to better coordinate the flow of goods and trains. The organisation of the three trucks in the loading area and the time consumption index are analysed, and the optimisation model of the train route adjustment is constructed based on the results to reduce the time consumption of train transportation. In order to ensure the spatial feasibility of the designed model in the application process, based on the improved genetic algorithm, the complexity of the built model and related constraints are considered, and an algorithm that restricts the space search is established. This algorithm can realise adaptive adjustment. The case analysis of Huangdao loading area proves the effect of this model.
引用
收藏
页码:480 / 502
页数:24
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