The electric vehicle routing problem with synchronized mobile partial recharging and non-strict waiting strategy
The electric vehicle routing problem with synchronized mobile partial recharging and non-strict waiting strategy
Many transportation activities have shifted to use electric vehicles (EVs) due to low-carbon and sustainability concerns. The main challenges faced by companies during the transition are the short range of EVs and the lack of recharging infrastructure. To cope with this situation, mobile charging vehicles (MCVs) are used in the system. However, this significantly increases the complexity of the electric vehicle routing problem (EVRP), as the routes for both EVs and MCVs should be optimized, and the two routes are highly interdependent. Moreover, most existing literature assumes that EVs need to be fully recharged or swapped, and EVs cannot wait for MCVs. This may lead to MCVs detour and increase scheduling difficulties, increasing the overall cost for both routes and reducing efficiency. Therefore, this paper proposes an EVRP model with synchronized mobile partial recharging and non-strict waiting strategy. The model relaxed the assumptions about full recharging and MCV waiting strategy, further increasing the complexity of the EVRP. To solve this model, we propose a two-stage dynamic programming and forward time slack algorithm based on the labeling algorithm, which is integrated into the framework of an improved adaptive large neighborhood search algorithm. Extensive numerical experiments are then conducted to demonstrate the efficiency of the algorithm and the benefits of the non-strict waiting strategy. Finally, the paper discusses some management insights based on the above analysis.
Xiao, Jianhua
0722e24e-61bc-42b8-878b-99b0b7e502c0
Liu, Xiaoyang
984baef1-b234-45df-8271-31b2f5be0257
Liu, Tao
0c29c130-c388-491c-81ef-a15a9349ac4b
Li, Na
99472966-c0ba-45b5-984d-35ff668a96e4
Martinez-Sykora, Toni
2f9989e1-7860-4163-996c-b1e6f21d5bed
Xiao, Jianhua
0722e24e-61bc-42b8-878b-99b0b7e502c0
Liu, Xiaoyang
984baef1-b234-45df-8271-31b2f5be0257
Liu, Tao
0c29c130-c388-491c-81ef-a15a9349ac4b
Li, Na
99472966-c0ba-45b5-984d-35ff668a96e4
Martinez-Sykora, Toni
2f9989e1-7860-4163-996c-b1e6f21d5bed
Xiao, Jianhua, Liu, Xiaoyang, Liu, Tao, Li, Na and Martinez-Sykora, Toni
(2024)
The electric vehicle routing problem with synchronized mobile partial recharging and non-strict waiting strategy.
Annals of Operations Research.
(In Press)
Abstract
Many transportation activities have shifted to use electric vehicles (EVs) due to low-carbon and sustainability concerns. The main challenges faced by companies during the transition are the short range of EVs and the lack of recharging infrastructure. To cope with this situation, mobile charging vehicles (MCVs) are used in the system. However, this significantly increases the complexity of the electric vehicle routing problem (EVRP), as the routes for both EVs and MCVs should be optimized, and the two routes are highly interdependent. Moreover, most existing literature assumes that EVs need to be fully recharged or swapped, and EVs cannot wait for MCVs. This may lead to MCVs detour and increase scheduling difficulties, increasing the overall cost for both routes and reducing efficiency. Therefore, this paper proposes an EVRP model with synchronized mobile partial recharging and non-strict waiting strategy. The model relaxed the assumptions about full recharging and MCV waiting strategy, further increasing the complexity of the EVRP. To solve this model, we propose a two-stage dynamic programming and forward time slack algorithm based on the labeling algorithm, which is integrated into the framework of an improved adaptive large neighborhood search algorithm. Extensive numerical experiments are then conducted to demonstrate the efficiency of the algorithm and the benefits of the non-strict waiting strategy. Finally, the paper discusses some management insights based on the above analysis.
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Accepted/In Press date: 20 May 2024
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Local EPrints ID: 490232
URI: http://eprints.soton.ac.uk/id/eprint/490232
ISSN: 0254-5330
PURE UUID: f90f76e6-e2c7-4b73-b8ee-aa95f641b0ef
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Date deposited: 20 May 2024 17:41
Last modified: 21 May 2024 01:43
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Author:
Jianhua Xiao
Author:
Xiaoyang Liu
Author:
Tao Liu
Author:
Na Li
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