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Reducing the transport footprint of last-mile logistics

Reducing the transport footprint of last-mile logistics
减少最后一英里物流的运输足迹
批准号:
2282405
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
翻译
当天送货的需求不断增长,而由于日益严重的拥堵,城市地区的旅行时间继续恶化。通常,在城市规划中很少考虑物流,也很少考虑日常递送所面临的环境负担。在多种更清洁的运输方式中转变为更可持续的做法可以帮助缓解部分压力。本研究旨在以索伦特地区的NHS当日递送系统为案例,研究多式联运物流车队在城市和城市周边环境中跨多种应用的潜力。来自多个NHS机构和地方政府的数据将为分析提供信息,以了解共享物流资产的可能性程度,以及对整体网络性能的影响。这项研究还将寻求拥抱无人机和电动自行车等现代技术,并了解它们减少当天递送的环境足迹的潜在范围。研究的部分内容将包括将医疗负担(如全科医生手术和患者/当地救护车流动的病理样本)与市议会负担(如图书馆书籍和学校膳食)相结合的优化挑战。将适当的车辆分配到适当的车辆以满足每次递送的标准对于维持或改善服务非常重要,因此将开发一个分配系统来支持这项研究。随着对这些挑战的更好理解,本研究将寻求找出有助于提高医疗保健物流效率和减少当前环境足迹的最佳模式组合。
英文摘要
The demand for same day deliveries is ever growing, whilst journey times in urban areas continue to worsen as a result of increasing congestion. Typically, little thought is given to logistics in urban planning, nor the environmental burden faced by everyday deliveries. Transfer to more sustainable practices across multiple, cleaner transit modes can help to relieve some of these pressures.This research aims to investigate the potential for a multi-modal logistics fleet to operate across many applications in an urban and peri-urban environment, using NHS same day delivery systems in the Solent region as case studies. Data from multiple NHS bodies and local government will inform analyses to understand the extent to which sharing logistics assets is plausible, and the implications for overall network performance. The research will also look to embrace modern technologies such as drones and e-Bikes and understand their potential scope for reducing the environmental footprint of same-day delivery.Part of the research will include the optimisation challenge of combining health care loads such as pathology samples from GP surgeries and patient/local ambulance movements, with city council loads such as library books and school meals.Allocations to appropriate vehicles to meet the criteria for each delivery is important to maintain or improve services, thus an allocation system will be developed to support this research. With a better understanding of these challenges, this research will seek to identify optimal combinations of mode which can help to improve the efficiency of health care logistics and reduce the current environmental footprint.
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