摘要
由于市郊客流在时空分布上存在不均衡的特点,单一交路、站站停列车不能很好地满足客流需求,因此根据市郊客流特点研究不同停站方案(如快慢车)、开行区段(如大小区段)组合的列车开行方案具有重要意义.本文在分析乘客出行广义费用的基础上,充分考虑列车开行方案与乘客选择之间的主从博弈关系,建立了市郊线路多交路快慢车开行方案的双层规划模型,并设计了遗传—模拟退火优化算法进行求解.在算例研究中,针对某一具体市郊线路,对结合大小交路、快慢车的列车开行方案进行优化,求解得出相对于传统的单一交路、站站停开行模式,多交路快慢车结合的开行方案使乘客的总旅行时间和企业运营成本分别降低了2.25%和9.25%,验证了本文模型和算法的实用性.
Due to the uneven temporal and spatial distribution of passenger flow, the train plan that stops at every station and runs along the entire line cannot well meet passenger flow demand. Therefore, according to the characteristics of passenger flow in suburban rail transit, a research on the train plan that combines full-length short-turn routing with express-local modes is of great significance. Based on the analysis of passengers＇ transfer behavior and generalized travel cost, this paper gives a full consideration of the master-slave game relationship between the train plan and passengers route choice, and then puts forward a bi-level programming model to obtain the train plan that aimed at solving the spatial disequilibrium of demand and eventually increase the line＇s capacity and service quality. In the case study, taking a specific suburban line as a numerical example, the train plan combined with multi-routing and express-local modes is obtained. Result shows that compared with traditional train plan with single-routing and local modes, the multi-routing and express-local modes have made the passengers＇ traveling time and enterprise＇s operation cost reduced by 2.25% and 9.25%, respectively. The model and the algorithm are proved effective.
作者
汤莲花
徐行方
TANG Lian-hua;XU Xing-fang(The Key Laboratory of Road and Traffic Engineering,Ministry of Education,Tongji University,Shanghai 201804,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2018年第3期152-159,共8页
Journal of Transportation Systems Engineering and Information Technology
关键词
城市交通
市郊轨道交通
开行方案
双层规划
快慢车
大小交路
遗传—模拟退火算法
urban traffic
suburban rail transit
train plan
bi-level programming
express-local modes
full-lengthand short-turn routing
genetic-simulated annealing optimization algorithm
