An Analysis on Optimizing Full and Part Routes of Urban Rail Transit under Peak Times
Jing Li, Mei Han, Guifeng Gao, Yifang Yan, Zijian Wang
Available Online May 2019.
- 10.2991/cnci-19.2019.87How to use a DOI?
- Urban rail transit, Full and part routes, Multi-objective planning, Genetic algorithm.
The cross-section passenger flow of urban rail transit has a large difference in space during the peak times and the operation mode of full and part routes should be adopted. By analyzing the passenger flow in the peak times, aiming at the minimum cost of the enterprise and the passenger waiting time, the multi-objective optimization model can be constructed. By introducing the time value coefficient, the passenger waiting time will be converted into the cost of generalized waiting time. The multi-objective optimization mode is transformed into a single-objective optimization model. The genetic algorithm is used to solve this problem and calculates the frequency of trains. Finally, the validity of the model is verified by an example.
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jing Li AU - Mei Han AU - Guifeng Gao AU - Yifang Yan AU - Zijian Wang PY - 2019/05 DA - 2019/05 TI - An Analysis on Optimizing Full and Part Routes of Urban Rail Transit under Peak Times BT - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019) PB - Atlantis Press SP - 627 EP - 634 SN - 2352-538X UR - https://doi.org/10.2991/cnci-19.2019.87 DO - 10.2991/cnci-19.2019.87 ID - Li2019/05 ER -