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时变路网下电动汽车冷链配送路径规划研究

本站小编 Free考研考试/2024-01-16

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温廷新,李可昕,赵琳琳,栗业,周甜,何燕.时变路网下电动汽车冷链配送路径规划研究[J].,2022,62(6):641-649
时变路网下电动汽车冷链配送路径规划研究
Research of route planning for electric vehicle cold chain distribution under time-varying road network
DOI:10.7511/dllgxb202206012
中文关键词:电动汽车多温共配生鲜品运输K-means聚类免疫遗传算法
英文关键词:electric vehiclemulti-temperature co-distributiontransportation of fresh productsK-means clusteringimmune genetic algorithm
基金项目:国家自然科学基金资助项目(71771111);山东省社会科学基金资助项目(20DGLJO14);辽宁省教学改革研究项目(辽教办2021254号).
作者单位
温廷新,李可昕,赵琳琳,栗业,周甜,何燕
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中文摘要:
在双碳背景下,电动汽车已在物流行业快速普及.在满足生鲜品的新鲜程度、车辆限载及电动汽车的电量限制等约束条件下,将电动汽车充电过程所产生成本纳入目标函数中,构建了时变路网下带软时间窗的电动汽车多温共配路径优化模型.根据该模型的特点,引入K-means聚类对客户进行聚类,同一聚类单元内设计免疫遗传算法,得到启发式路径优化方案.实验结果表明,根据顾客的需要及时变路网特性,合理安排运输规划与配送路径,保证了生鲜品运输的时效性;采用电动汽车多温共配的运输方式进行运输,运输成本更加低廉、过程更加节能,提高了企业的经济效应.
英文摘要:
In the context of dual carbon, electric vehicles have been rapidly popularized in the logistics industry. Under the constraints of freshness of fresh products, vehicle load limit and electric power limit of electric vehicles, the cost of electric vehicle charging process is included in the objective function, and a multi-temperature co-distribution route optimization model of electric vehicles with soft time window under time-varying road network is constructed. According to the characteristics of the model, K-means clustering is introduced to cluster customers, immune genetic algorithm is designed in the same clustering unit, and the heuristic path optimization scheme is obtained. The experimental results show that according to the needs of customers and the characteristics of time-varying road network, the transportation planning and distribution route is reasonably arranged to ensure the timeliness of fresh product transportation; The multi-temperature co-distribution transportation mode of electric vehicles makes the transportation cost cheaper and the process more energy-saving, and improves the economic effect of the enterprise.
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