Data Intelligence for Logistics

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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.