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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Main Authors: Seyed Sajjad Fazeli, Saravanan Venkatachalam, Jonathon M. Smereka
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2024-01-01
Series:Sustainable Operations and Computers
Subjects:
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.
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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