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| A hybrid genetic algorithm for the electric vehicle routing problem with time windows |
| QixingLiu1,PengXu1,YuhuWu1,TielongShen2 |
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| (1 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China;2 Department of Mechanical Engineering, Sophia University, Tokyo 102-8554, Japan) |
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| 摘要: |
| Driven by the newlegislation on greenhouse gas emissions, carriers began to use electric vehicles (EVs) for logistics transportation.
This paper addresses an electric vehicle routing problem with time windows (EVRPTW). The electricity consumption
of EVs is expressed by the battery state-of-charge (SoC). To make it more realistic, we take into account the terrain grades
of roads, which affect the travel process of EVs. Within our work, the battery SoC dynamics of EVs are used to describe this
situation. We aim to minimize the total electricity consumption while serving a set of customers. To tackle this problem, we
formulate the problem as a mixed integer programming model. Furthermore, we develop a hybrid genetic algorithm (GA) that
combines the 2-opt algorithm with GA. In simulation results, by the comparison of the simulated annealing (SA) algorithm
and GA, the proposed approach indicates that it can provide better solutions in a short time. |
| 关键词: Electric vehicles · Vehicle routing · Battery SoC · Hybrid genetic algorithm |
| DOI：https://doi.org/10.1007/s11768-022-00091-1 |
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| 基金项目: |
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| A hybrid genetic algorithm for the electric vehicle routing problem with time windows |
| Qixing Liu1,Peng Xu1,Yuhu Wu1,Tielong Shen2 |
| (1 School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China;2 Department of Mechanical Engineering, Sophia University, Tokyo 102-8554, Japan) |
| Abstract: |
| Driven by the newlegislation on greenhouse gas emissions, carriers began to use electric vehicles (EVs) for logistics transportation.
This paper addresses an electric vehicle routing problem with time windows (EVRPTW). The electricity consumption
of EVs is expressed by the battery state-of-charge (SoC). To make it more realistic, we take into account the terrain grades
of roads, which affect the travel process of EVs. Within our work, the battery SoC dynamics of EVs are used to describe this
situation. We aim to minimize the total electricity consumption while serving a set of customers. To tackle this problem, we
formulate the problem as a mixed integer programming model. Furthermore, we develop a hybrid genetic algorithm (GA) that
combines the 2-opt algorithm with GA. In simulation results, by the comparison of the simulated annealing (SA) algorithm
and GA, the proposed approach indicates that it can provide better solutions in a short time. |
| Key words: Electric vehicles · Vehicle routing · Battery SoC · Hybrid genetic algorithm |
