Electric Vehicle Tour Planning Considering Range Anxiety
被引:30
作者:
Chen, Rui
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Chen, Rui
[1
,2
]
Liu, Xinglu
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Liu, Xinglu
[3
]
Mia, Lixin
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R China
Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Mia, Lixin
[2
,3
]
Yang, Peng
论文数: 0引用数: 0
h-index: 0
机构:
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Yang, Peng
[2
]
机构:
[1] Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R China
[3] Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R China
electric vehicle;
tour planning;
range anxiety;
bi-objective programming;
TRAVELING SALESMAN PROBLEM;
CONSTRAINED TRAFFIC ASSIGNMENT;
TEAM ORIENTEERING PROBLEM;
ROUTING PROBLEM;
TIME WINDOWS;
ALGORITHM;
STRATEGIES;
HEURISTICS;
IMPACT;
D O I:
10.3390/su12093685
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
In this study, the tour planning problem for electric vehicles is investigated. We aim to derive the optimal route and thus, to maximize profitability and minimize range anxiety within the time horizon. To solve this problem, a bi-objective mixed integer model is proposed. Specifically, we first introduced the reliability of route planning and quantified it as a cost with specific functions. The nonlinear model was then converted into a bi-objective mixed integer linear program, and an interactive branch and bound algorithm was adopted. Numerical experiments conducted on different networks have shown that the model that considers range anxiety offers more effective solutions. This means that our model is able to plan the routes with high reliability and low risk of profit loss and accidents.