Last Mile Logistics and the Shared Economy: Developing dynamic vehicle routing algorithms that adopt unsupervised learning for novel last-mile initiat

最后一英里物流和共享经济：开发动态车辆路线算法，采用无监督学习来实现新颖的最后一英里启动

• 批准号: 2579363
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2579363
• 关键词: Last; Mile; Logistics; Shared; Economy

This PhD aims to investigate how innovation can shape last-mile logistics and develop a modelling framework that could accommodate these developments. This work seeks to establish whether novel last-mile solutions (Crowdshipping, Public Transport Piggybacking Van-Sharing) could harmonise economic efficiency with environmental sustainability in urban environments. Hence, this work will explore how each solution affects energy consumption, network efficiency and air pollution. The investigation will model the solution on a simulation testbed with varying input parameters (network congestion, demand-levels, etc.).

该博士旨在调查创新如何塑造最后一英里的物流并开发可以适应这些发展的建模框架。这项工作旨在确定新颖的最后一英里解决方案（众筹，公共交通工具共享）是否可以将经济效率与城市环境中的环境可持续性保持一致。因此，这项工作将探讨每个解决方案如何影响能源消耗，网络效率和空气污染。该研究将在模拟测试中对解决方案进行建模，其中输入参数（网络拥塞，需求级等）。