A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system
文献类型:期刊论文
作者 | Liu, Hongjie2,3,4; Tang, Tao2,3; Guo XW(郭希旺)1,4,6; Xia, Xisheng5 |
刊名 | ADVANCES IN MECHANICAL ENGINEERING
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出版日期 | 2018 |
卷号 | 10期号:9页码:1-13 |
关键词 | Regenerative energy utilization timetable optimization headway time dwell time artificial bee colony |
ISSN号 | 1687-8140 |
产权排序 | 4 |
英文摘要 | 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. |
WOS关键词 | BRAKING ENERGY ; PERFORMANCE ; STRATEGIES ; MANAGEMENT ; FLOW |
资助项目 | National Key Research and Development Program of China[2018YFB1201501] ; Beijing municipal natural science foundation[L161008] ; Fundamental Research Funds for the Central Universities[2016JBZ004] ; TCT Funding Program[9907006510] ; Chinese Railway Certification Center funding program[1852ZJ1303] ; Beijing Laboratory of Urban Rail Transit ; China Scholarship Council |
WOS研究方向 | Thermodynamics ; Engineering |
语种 | 英语 |
WOS记录号 | WOS:000445224400001 |
资助机构 | National Key Research and Development Program of China ; Beijing municipal natural science foundation ; Fundamental Research Funds for the Central Universities ; TCT Funding Program ; Chinese Railway Certification Center funding program ; Beijing Laboratory of Urban Rail Transit ; China Scholarship Council |
源URL | [http://ir.sia.cn/handle/173321/22819] ![]() |
专题 | 沈阳自动化研究所_数字工厂研究室 |
通讯作者 | Liu, Hongjie; Guo XW(郭希旺) |
作者单位 | 1.Computer and Communication Engineering College, Liaoning Shihua University, Fushun, China 2.School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China 3.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China 4.Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA 5.Research and Development Center, Traffic Control Technology Co., Ltd., Beijing, China 6.Key Laboratory of Network Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Liaoning, China |
推荐引用方式 GB/T 7714 | Liu, Hongjie,Tang, Tao,Guo XW,et al. A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system[J]. ADVANCES IN MECHANICAL ENGINEERING,2018,10(9):1-13. |
APA | Liu, Hongjie,Tang, Tao,Guo XW,&Xia, Xisheng.(2018).A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system.ADVANCES IN MECHANICAL ENGINEERING,10(9),1-13. |
MLA | Liu, Hongjie,et al."A timetable optimization model and an improved artificial bee colony algorithm for maximizing regenerative energy utilization in a subway system".ADVANCES IN MECHANICAL ENGINEERING 10.9(2018):1-13. |
入库方式: OAI收割
来源:沈阳自动化研究所
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