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考虑电动汽车充电选择的配送路径优化研究

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由于人们环保意识的不断增强以及国家对新能源技术应用的支持,电动汽车在城市物流"最后一公里"中得到了广泛应用.但是,电动汽车电池续航里程短、充电时间长以及配套设施不足等问题,阻碍了其在实际应用中的普及与推广.为了解决电动汽车物流配送路径优化的问题,采用了客户点可充电功能分类的策略,构建了一个考虑电动汽车充电选择的配送路径优化模型,并设计了混合模拟退火遗传算法来求解.最后,通过算例仿真验证了模型和算法的有效性.
Research on Distribution Route Optimization Considering Electric Vehicle Charging Selection
With the increasing awareness of environmental protection and the support of the state for the application of new energy technology,electric vehicles are widely used in the"last kilometer"of urban logistics.However,due to the shortage of battery life,long charging time and inadequate supporting facilities,the application and promotion of electric vehicles in the real society are seriously hampered.For this reason,in order to optimize the distribution route of EV,by introducing the strategy of customer point rechargeable function classification,the distribution route optimization model considering the charging choice of EV is established,and the hybrid simulated annealing genetic algorithm is designed to solve the problem.Finally,the validity of the model and algorithm is verified and analyzed by numerical simulation.

electric vehicle distributioncharging selectionhybrid simulated annealing genetic algorithms

葛显龙、李祖伟

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重庆交通大学经济与管理学院,重庆 400074

电动汽车配送 充电选择 混合模拟退火遗传算法

国家社会科学基金国家社会科学基金教育部人文社会科学基金博士后科学基金特别资助重庆市基础与前沿研究项目重庆市教委人文社会科学研究项目重庆市科学技术研究项目

71502021717020162014YJC6300382016T90862cstc2016jcyjA016019JD033KJ1500702

2024

数学的实践与认识
中国科学院数学与系统科学研究院

数学的实践与认识

CSTPCD北大核心
影响因子：0.349
ISSN：1000-0984
年,卷(期)：2024.54(3)
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