Modelling and analysis of emergent technologies in logistics and distribution

点击翻译按钮获取中文摘要

The e-commerce market has seen an unprecedented growth in Canada and world-wide. Global e-retail sales were valued at $2.3 trillion US in 2017 and are expected to reach 4.9 trillion in 2021 (Statista 2019). In Canada, e-commerce represented 7.3% of total retail in 2017, increasing from 4.5% in 2013. This growth is pushing the industry to optimize last mile operations and adopt innovative technologies to enable cost-effective same-day delivery. Industry experts as well as major e-retailers recognize that same-day delivery represents a major competitive advantage as it combines the convenience of ordering online and the immediacy of shopping at the store. However, it should be offered free or at minimal cost to become the standard of last mile delivery in the future. While there is a large body of literature on distribution planning for e-retailing, novel technologies, such as multi-modal, drone, and crowdsourced delivery, create new challenges both in terms of modelling and optimization. There is limited work that explicitly examines problems arising from crowdsourced last mile delivery and the assumptions do not reflect industry trends. Similarly, most of the research on drone delivery focuses on operational aspects and ignores the tactical and strategic issues like feasibility, profitability, and capacity planning. Same day and last mile deliveries are characterized by short service times, uncertainty in demand which may arrive dynamically, and uncertainty in supply as is the case in crowdsourced delivery. These features call for new models and new solution methods that are fast and reliable. The research program aims to address new problems that have not been studied in the literature, and to develop appropriate models and solution methods to enable the effective use of the new technologies. In particular, the dynamic and uncertain aspects of same-day delivery lead to complex optimization problems that challenge the state-of-the-art. The e-retailing industry generates an abundance of data on all aspects of operation from demand, to weather and traffic conditions, to supply, that is underutilized at best. Transforming this data into information provides a golden opportunity to create competitive advantage for Canadian and global e-retailers. Data may be used to assess, optimize, and validate operations, processes, and business strategies. We will combine data availability with the improvements in computational power to build realistic data-driven optimization models and solution methods. These are bound to benefit dynamic and uncertain systems that go beyond logistics such as telecommunications and emergency medical service systems. Through this program, seven HQP will be trained in quantitative problem solving and data analytics skills in data analysis, prediction, and action prescription. These skills are very much sought by Canadian employers in such industries as logistics and supply chain, banking, health care, and consulting.