A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system
Document Type
Article
Publication Date
9-1-2018
Abstract
Maximizing regenerative energy utilization in subway systems has become a hot research topic in recent years. By coordinating traction and braking trains in a substation, regenerative energy is optimally utilized and thus energy consumption from the substation can be reduced. This article proposes a timetable optimization problem to maximize regenerative energy utilization in a subway system with headway and dwell time control. We formulate its mathematical model, and some required constraints are considered in the model. To keep the operation time duration constant, the headway time between different trains can be different. An improved artificial bee colony algorithm is designed to solve the problem. Its main procedure and some related tasks are presented. Numerical experiments based on the data from a subway line in China are conducted, and improved artificial bee colony is compared with a genetic algorithm. Experimental results prove the correctness of the mathematical model and the effectiveness of improved artificial bee colony, which improves regenerative energy utilization for the experimental line and performs better than genetic algorithm.
Identifier
85054131123 (Scopus)
Publication Title
Advances in Mechanical Engineering
External Full Text Location
https://doi.org/10.1177/1687814018797034
e-ISSN
16878140
ISSN
16878132
Issue
9
Volume
10
Grant
1852ZJ1303
Fund Ref
China Scholarship Council
Recommended Citation
Liu, Hongjie; Tang, Tao; Guo, Xiwang; and Xia, Xisheng, "A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system" (2018). Faculty Publications. 8425.
https://digitalcommons.njit.edu/fac_pubs/8425
