| A hybrid genetic algorithm for the electric vehicle routing problem with time windows |
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| 作者姓名： | Qixing Liu Peng Xu Yuhu Wu Tielong Shen |
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| 作者单位： | 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.
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| 关 键 词： | Electric vehicles · Vehicle routing · Battery SoC · Hybrid genetic algorithm |
A hybrid genetic algorithm for the electric vehicle routing problem with time windows |
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| Qixing Liu,Peng Xu,Yuhu Wu,Tielong Shen.A hybrid genetic algorithm for the electric vehicle routing problem with time windows[J].Journal of Control Theory and Applications,2022,20(2):279-286. |
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| Authors: | Qixing Liu Peng Xu Yuhu Wu Tielong Shen |
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| Affiliation: | 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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| 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. |
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| Keywords: | |
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