Efficient algorithms for electric vehicles’ min-max routing problem
An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co. Ltd.
2024-01-01
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| Series: | Sustainable Operations and Computers |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666412723000107 |
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| author | Seyed Sajjad Fazeli Saravanan Venkatachalam Jonathon M. Smereka |
| author_facet | Seyed Sajjad Fazeli Saravanan Venkatachalam Jonathon M. Smereka |
| author_sort | Seyed Sajjad Fazeli |
| collection | DOAJ |
| description | An increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with EVs to strengthen the efforts for sustainable and environment-friendly operations. However, deploying a fleet of EVs asks for efficient routing and recharging strategies to alleviate their limited range and mitigate the battery degradation rate. In this work, a fleet of electric vehicles is considered for transportation and logistic capabilities with limited battery capacity and scarce charging station availability. We introduce a min-max electric vehicle routing problem (MEVRP) where the maximum distance traveled by any EV is minimized while considering charging stations for recharging. We propose an efficient branch and cut framework and a three-phase hybrid heuristic algorithm that can efficiently solve a variety of instances. Extensive computational results and sensitivity analyses are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively. Finally a data-driven simulation implemented with the robot operating system (ROS) middleware are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively. |
| format | Article |
| id | doaj-art-05f5dc9f49bb46dc9b0a0e2f9fd6f9d2 |
| institution | Kabale University |
| issn | 2666-4127 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Sustainable Operations and Computers |
| spelling | doaj-art-05f5dc9f49bb46dc9b0a0e2f9fd6f9d22024-11-30T07:14:07ZengKeAi Communications Co. Ltd.Sustainable Operations and Computers2666-41272024-01-0151528Efficient algorithms for electric vehicles’ min-max routing problemSeyed Sajjad Fazeli0Saravanan Venkatachalam1Jonathon M. Smereka2Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USACorresponding author at Distribution A. Approved for public release distribution is unlimited. OPSEC # 4492.; Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USAResearcher within the Ground Vehicle Robotics (GVR) team, U.S. Army CCDC Ground Vehicle Systems Center (GVSC), Warren, MI, USAAn increase in greenhouse gases emission from the transportation sector has led companies and the government to elevate and support the production of electric vehicles (EV). With recent developments in urbanization and e-commerce, transportation companies are replacing their conventional fleet with EVs to strengthen the efforts for sustainable and environment-friendly operations. However, deploying a fleet of EVs asks for efficient routing and recharging strategies to alleviate their limited range and mitigate the battery degradation rate. In this work, a fleet of electric vehicles is considered for transportation and logistic capabilities with limited battery capacity and scarce charging station availability. We introduce a min-max electric vehicle routing problem (MEVRP) where the maximum distance traveled by any EV is minimized while considering charging stations for recharging. We propose an efficient branch and cut framework and a three-phase hybrid heuristic algorithm that can efficiently solve a variety of instances. Extensive computational results and sensitivity analyses are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively. Finally a data-driven simulation implemented with the robot operating system (ROS) middleware are performed to corroborate the efficiency of the proposed approach, both quantitatively and qualitatively.http://www.sciencedirect.com/science/article/pii/S2666412723000107Electric vehiclesRoutingCharging stationHybrid heuristicVariable neighborhood search |
| spellingShingle | Seyed Sajjad Fazeli Saravanan Venkatachalam Jonathon M. Smereka Efficient algorithms for electric vehicles’ min-max routing problem Sustainable Operations and Computers Electric vehicles Routing Charging station Hybrid heuristic Variable neighborhood search |
| title | Efficient algorithms for electric vehicles’ min-max routing problem |
| title_full | Efficient algorithms for electric vehicles’ min-max routing problem |
| title_fullStr | Efficient algorithms for electric vehicles’ min-max routing problem |
| title_full_unstemmed | Efficient algorithms for electric vehicles’ min-max routing problem |
| title_short | Efficient algorithms for electric vehicles’ min-max routing problem |
| title_sort | efficient algorithms for electric vehicles min max routing problem |
| topic | Electric vehicles Routing Charging station Hybrid heuristic Variable neighborhood search |
| url | http://www.sciencedirect.com/science/article/pii/S2666412723000107 |
| work_keys_str_mv | AT seyedsajjadfazeli efficientalgorithmsforelectricvehiclesminmaxroutingproblem AT saravananvenkatachalam efficientalgorithmsforelectricvehiclesminmaxroutingproblem AT jonathonmsmereka efficientalgorithmsforelectricvehiclesminmaxroutingproblem |