课题基金 / 基金详情

Data Intelligence for Logistics

Data Intelligence for Logistics
物流数据智能
批准号:
538506-2019
负责人:
RobertFrejinger, EmmaE
金额:
$14.5万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
Purolator是加拿大一家提供快递包裹递送服务的公司,在面对激烈的竞争和电子商务服务的扩张等日益增长的挑战时,必须不断改进其业务以满足客户的需求,同时保持其效率。该公司特别感兴趣的是分析执行其业务的替代方法,以减少其成本和环境足迹,同时提高其服务质量。这个为期5年的项目延续了2015年开始的Purolator与加拿大运输和物流领域领先的研究人员之间的合作。公司面临的挑战汇集了来自运筹学、土木工程和数据科学的专家,共同致力于开发方法和决策软件工具,以造福公司。该项目分为五个区域:1.;城市物流。该领域专注于第一英里/最后一英里配送的设计、规划和运营,特别是在市中心地区。2. 全国/区域配电网规划。该领域致力于通过整合与枢纽位置和枢纽间多式联运(空运)运输相关的决策,开发规划国家/区域分销网络的优化模型。3. 供应链优化。该领域通过研究市场以及如何通过创新物流概念提供的各种服务尽可能有效地满足需求,关注同步供应与需求的最佳方法。4. 新技术对网络优化的影响。在这一领域,我们研究了新技术对快递包裹递送服务的影响。新技术包括传感器的部署和创新交通工具的可用性,如自动穿梭巴士和无人机。5. 新经济的分销网络。该领域强调开发模型来设计和管理协作平台,以改善公司的物流。
英文摘要
Purolator, a Canadian company offering express package delivery services, has to improve its operations on a continuous basis in order to satisfy its customers, while maintaining its efficiency in the face of ever-growing challenges such as fierce competition and the expansion of e-commerce services. The company is particularly interested in the analysis of alternative ways to perform its operations that would reduce its costs and its environmental footprint, while improving its quality of service. This 5-year project pursues and significantly extends a collaboration that started in 2015 between Purolator and a group of leading Canadian researchers in transportation and logistics. The challenges faced by the company bring together specialists from operations research, civil engineering and data science, united towards the goal of developing methodology and decision-making software tools to the benefit of the company. The project is divided into five areas: 1. City Logistics. This area focuses on the design, planning and operations of First Mile/Last Mile distribution, in particular in downtown areas. 2. National/Regional Distribution Network Planning. This area is dedicated to the development of optimization models for planning national/regional distribution networks by integrating decisions related to hub locations and inter-hub multi-modal (air-truck) transportation. 3. Supply Chain Optimization. This area is concerned with the best ways to synchronize supply with demand, by studying the market and how demand can be met as efficiently as possible using various types of services that can be offered through innovative logistics concepts. 4. Impact of New Technologies on Network Optimization. In this area, we study the impact of new technologies on the express package delivery services. New technologies include the deployment of sensors and the availability of innovative vehicles, such as autonomous shuttles and drones. 5. Distribution Networks for the New Economy. This area emphasizes the development of models to design and manage collaborative platforms to improve the logistics of the company.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金