Pickup and delivery problem with electric vehicles and time windows considering queues

皮卡 排队 计算机科学 汽车工程 工程类 运输工程 模拟 计算机网络 人工智能 图像(数学)
作者
Saiqi Zhou,Dezhi Zhang,Wentao Yuan,Zhenjie Wang,Likun Zhou,Michael G.H. Bell
出处
期刊:Transportation Research Part C-emerging Technologies [Elsevier BV]
卷期号:167: 104829-104829 被引量:14
标识
DOI:10.1016/j.trc.2024.104829
摘要

The electric vehicle, as a green and sustainable technology, has gained tremendous development and application recently in the logistics distribution system. However, the increasing workload and limited infrastructure capacity pose challenges for electric vehicles in the pickup and delivery operating system, including task allocation, electric vehicle routing, and queue scheduling. To address these issues, this paper introduces a pickup and delivery problem with electric vehicles and time windows considering queues, which considers queue scheduling for multiple electric vehicles when operating at the same site. A novel mixed integer linear programming model is proposed to minimize the cost of travel distance and queue time. An adaptive hybrid neighborhood search algorithm is developed to solve the moderately large-scale problem. Experimental results demonstrate the effectiveness of the model and adaptive hybrid neighborhood search algorithm. The competitive performance of the developed algorithm is further confirmed by finding 9 new best solutions for the pickup and delivery problem with electric vehicles and time windows benchmark instances. Moreover, the results and sensitivity analysis of objective weight costs highlight the impact and importance of considering queues in the studied problem and obtain some management insights. • A PDP with EVs and time windows considering queues is introduced. • A MILP model is proposed to minimize the cost of travel distance and queue time. • An adaptive hybrid neighborhood search algorithm is developed to solve the problem. • New best solutions for instances of the PDP with EVs and time windows are obtained. • Analysis shows the importance of considering queues and some management insights.
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