Modelling and analysis of emergent technologies in logistics and distribution

电子商务市场在加拿大和世界范围内都出现了前所未有的增长。2017年，全球电子零售额为2.3万亿美元，预计2021年将达到4.9万亿美元（Statista 2019）。在加拿大，2017年电子商务占零售总额的7.3%，高于2013年的4.5%。这一增长正在推动行业优化最后一英里运营，并采用创新技术，以实现具有成本效益的当日交付。 行业专家以及主要的电子零售商认识到，当日送达是一个主要的竞争优势，因为它结合了在线订购的便利性和在商店购物的即时性。然而，它应该免费或以最低成本提供，以成为未来最后一英里交付的标准。 虽然有大量关于电子零售分销规划的文献，但多模式、无人机和众包交付等新技术在建模和优化方面都带来了新的挑战。明确研究众包最后一英里交付所产生的问题的工作有限，并且假设并不反映行业趋势。同样，大多数关于无人机交付的研究都集中在操作方面，而忽略了可行性、盈利能力和容量规划等战术和战略问题。同一天和最后一英里交付的特点是服务时间短，需求的不确定性可能会动态到达，以及供应的不确定性，就像众包交付的情况一样。这些特征要求快速可靠的新模型和新解决方案。该研究计划旨在解决文献中尚未研究的新问题，并开发适当的模型和解决方法，以有效利用新技术。特别是，当天交付的动态和不确定性方面导致复杂的优化问题，挑战国家的最先进的电子零售业产生了大量的数据，从需求的各个方面的操作，天气和交通条件，供应，这是最好的利用不足。将这些数据转化为信息提供了一个黄金机会，为加拿大和全球电子零售商创造竞争优势。数据可用于评估、优化和验证运营、流程和业务策略。我们将联合收割机的数据可用性与计算能力的提高相结合，以建立现实的数据驱动的优化模型和解决方案。这必将使电信和紧急医疗服务系统等物流之外的动态和不确定系统受益。通过该计划，七名HQP将接受数据分析，预测和行动处方方面的定量问题解决和数据分析技能的培训。这些技能是加拿大雇主在物流和供应链，银行，医疗保健和咨询等行业非常需要的。

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.