Electric Vehicle Routing Problem with Charging Time and Variable Travel Time
An electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging...
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Hindawi Limited
2017-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2017/5098183 |
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doaj-51997ffd238f43808e8d52af97deb2ac2020-11-24T21:07:55ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472017-01-01201710.1155/2017/50981835098183Electric Vehicle Routing Problem with Charging Time and Variable Travel TimeSai Shao0Wei Guan1Bin Ran2Zhengbing He3Jun Bi4School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaDepartment of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USASchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaAn electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging plan. Meanwhile, a dynamic Dijkstra algorithm is applied to find the shortest path between any two adjacent nodes along the routes. To prevent the depletion of all battery power and ensure safe operation in transit, electric vehicles with insufficient battery power can be repeatedly recharged at charging stations. The fluctuations in travel time are implemented to reflect a dynamic traffic environment. In conclusion, a large and realistic case study with a road network in the Beijing urban area is conducted to evaluate the model performance and the solution technology and analyze the results.http://dx.doi.org/10.1155/2017/5098183 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sai Shao Wei Guan Bin Ran Zhengbing He Jun Bi |
spellingShingle |
Sai Shao Wei Guan Bin Ran Zhengbing He Jun Bi Electric Vehicle Routing Problem with Charging Time and Variable Travel Time Mathematical Problems in Engineering |
author_facet |
Sai Shao Wei Guan Bin Ran Zhengbing He Jun Bi |
author_sort |
Sai Shao |
title |
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time |
title_short |
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time |
title_full |
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time |
title_fullStr |
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time |
title_full_unstemmed |
Electric Vehicle Routing Problem with Charging Time and Variable Travel Time |
title_sort |
electric vehicle routing problem with charging time and variable travel time |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2017-01-01 |
description |
An electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging plan. Meanwhile, a dynamic Dijkstra algorithm is applied to find the shortest path between any two adjacent nodes along the routes. To prevent the depletion of all battery power and ensure safe operation in transit, electric vehicles with insufficient battery power can be repeatedly recharged at charging stations. The fluctuations in travel time are implemented to reflect a dynamic traffic environment. In conclusion, a large and realistic case study with a road network in the Beijing urban area is conducted to evaluate the model performance and the solution technology and analyze the results. |
url |
http://dx.doi.org/10.1155/2017/5098183 |
work_keys_str_mv |
AT saishao electricvehicleroutingproblemwithchargingtimeandvariabletraveltime AT weiguan electricvehicleroutingproblemwithchargingtimeandvariabletraveltime AT binran electricvehicleroutingproblemwithchargingtimeandvariabletraveltime AT zhengbinghe electricvehicleroutingproblemwithchargingtimeandvariabletraveltime AT junbi electricvehicleroutingproblemwithchargingtimeandvariabletraveltime |
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1716761548073992192 |