绿色物流中的电动汽车充电调度：挑战、途径与机遇
Electric Vehicle Charging Scheduling in Green Logistics: Challenges, Approaches and Opportunities
摘要：
用电动汽车取代化石燃料汽车可以在车辆的使用寿命期间将温室气体排放量减半，并减少城市地区的噪音污染。在绿色物流中，合理的充电计划确保了运输和电力系统的高效运行，同时为驾驶员提供经济和满意的充电服务。本文通过分析绿色物流中电动汽车充电调度问题的特点，结合空间分配、路径选择和能源管理等典型应用案例，对当前绿色物流中电动汽车充电调度问题进行了分类，并讨论了其面临的挑战，即：信息的可用性和利益相关者的战略行为，出现在随机和分散的环境中，并分类现有的方法，集中式，分布式和分散的，适用于这些挑战。此外，我们讨论了研究机会，应用基于市场的机制，这将与随机优化和机器学习协调，分散的，动态的和数据驱动的收费调度问题的管理未来的绿色物流。
英文摘要：
Replacing a fossil fuel-powered car with an electric model can halve greenhouse gas emissions over the course of the vehicle's lifetime and reduce the noise pollution in urban areas. In green logistics, a well-scheduled charging ensures an efficient operation of transportation and power systems and, at the same time, provides economical and satisfactory charging services for drivers. This paper presents a taxonomy of current electric vehicle charging scheduling problems in green logistics by analyzing its unique features with some typical use cases, such as space assignment, routing and energy management; discusses the challenges, i.e., the information availability and stakeholders' strategic behaviors that arise in stochastic and decentralized environments; and classifies the existing approaches, as centralized, distributed and decentralized ones, that apply to these challenges. Moreover, we discuss research opportunities in applying market-based mechanisms, which shall be coordinated with stochastic optimization and machine learning, to the decentralized, dynamic and data-driven charging scheduling problems for the management of the future green logistics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
