An Analysis on Optimizing Full and Part Routes of Urban Rail Transit under Peak Times

DOI

10.2991/cnci-19.2019.87How to use a DOI?

Keywords

Urban rail transit, Full and part routes, Multi-objective planning, Genetic algorithm.

Abstract

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.

Copyright

© 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/).

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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  -