Robust Service and Charging Plan for Dynamic Electric Demand-Responsive Transit Systems

被引:6
作者
Li, Xin [1 ,2 ]
Guan, Yu [3 ]
Huang, Jingou [3 ]
Yuan, Yun [3 ]
机构
[1] Dalian Maritime Univ, Coll Transportat Engn, Dalian 116026, Peoples R China
[2] Dalian Maritime Univ, Collaborat Innovat Ctr Transport Study, Dalian 116026, Peoples R China
[3] Dalian Maritime Univ, Coll Transportat Engn, Dalian 116026, Peoples R China
基金
中国国家自然科学基金;
关键词
Electric vehicles; Electrification; dynamic demand; demand-responsive transit; robust; VEHICLE-ROUTING PROBLEM; DIAL-A-RIDE; CLUSTERING APPROACH; TIME WINDOWS; OPTIMIZATION; ALGORITHMS; REDUCTION;
D O I
10.1109/TITS.2023.3321745
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study proposes a robust route optimization model for electric Demand-Responsive Transit (e-DRT) services, where dispatched vehicles may deviate from the determined plan to serve real-time demands. In particular, online partial charging strategies are coordinated with flexible service schedules. To benefit the productivity of the e-DRT system, the route schedule and charging time are changed dynamically. A two-phase Adaptive Large Neighborhood Search (ALNS) -based heuristic is proposed to effectively solve the proposed problem. The baseline case and large-scale cases are presented to verify the effectiveness and accuracy of the proposed method. Comparisons between CPLEX and the proposed algorithm suggest that the proposed algorithm can considerably improve computational efficiency. A comparative analysis shows the proposed model takes 21% less total cost than the alternative non-robust model. Further, two sensitivity tests are designed to unveil the impacts of unmet real-time requests and the charging rate on the e-DRT's performance.
引用
收藏
页码:15930 / 15947
页数:18
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