Data Intelligence for Logistics
Data Intelligence for Logistics
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
中文摘要
Purolator是一家提供快递包裹递送服务的加拿大公司,它必须不断改善运营,以满足客户的需求,同时在激烈竞争和电子商务服务扩张等日益增长的挑战中保持效率。该公司尤其感兴趣的是分析执行其运营的替代方法,这些方法将在提高服务质量的同时降低成本和环境足迹。这个为期5年的项目是Purolator和一群领先的加拿大运输和物流研究人员于2015年开始的合作的延续和极大的延伸。该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,朝着开发有利于公司的方法学和决策软件工具的目标团结在一起。项目分为五个方面:1.城市物流。这一领域的重点是第一英里/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/地区分销网络规划。该领域致力于通过整合与枢纽选址和枢纽间多式联运(空中-卡车)运输有关的决策,开发规划国家/区域分销网络的优化模型。3.供应链优化。这一领域通过研究市场以及如何利用可通过创新物流概念提供的各种类型的服务尽可能有效地满足需求,来研究使供应与需求同步的最佳方式。4.新技术对网络优化的影响。在这方面,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车辆的可用性,如自动航天飞机和无人机。5.面向新经济的分销网络。这方面的重点是开发模型,以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.
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