Modelling and analysis of emergent technologies in logistics and distribution

物流配送新兴技术的建模与分析

• 批准号: RGPIN-2020-04498
• 负责人: Gzara, Fatma
• 金额: $ 3.13万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758145
• 关键词: Modelling; analysis; emergent; technologies; logistics

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.

电子商务市场在加拿大和全球范围内实现了前所未有的增长。 2017年，全球电子零售销售额为23万亿美元，预计2021年将达到4.9万亿美元（Statista 2019）。在加拿大，电子商务占2017年总零售价的7.3％，从2013年的4.5％增加。这种增长促使该行业促使该行业优化上一英里的运营并采用创新技术，以实现成本效益的当天交付。行业专家以及主要的电子零售商认识到，当天交付是一个主要的竞争优势，因为它结合了在线订购和在商店购物的即时性的便利性。但是，应该免费提供或以最低成本提供将来成为最后一英里交付的标准。尽管有大量有关电子零售的分销计划的文献，但新型技术（例如多模式，无人机和众包交付），但在建模和优化方面都引起了新的挑战。有限的工作有限，可以明确研究由众包上一英里交付引起的问题，并且假设并不能反映行业趋势。同样，关于无人机交付的大多数研究都集中在操作方面，而忽略了战术和战略问题，例如可行性，盈利能力和能力计划。同一天和最后一英里的交付的特征是服务时间短，需求不确定性可能会动态到达以及供应不确定性，就像众包交付的情况一样。这些功能要求快速可靠的新型号和新的解决方案方法。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案方法以有效地使用新技术。特别是，当天交付的动态和不确定的方面导致了挑战最先进的复杂优化问题。电子零售行业对从需求到天气和交通状况到供应的所有运营各个方面都产生了大量数据，最多可以充分利用这种数据。将这些数据转换为信息为加拿大和全球电子零售商创造竞争优势提供了千载难逢的机会。数据可用于评估，优化和验证运营，流程和业务策略。我们将将数据可用性与计算能力的改进相结合，以构建现实的数据驱动的优化模型和解决方案方法。这些必定会受益于超越物流（例如电信和紧急医疗服务系统）的动态和不确定系统。通过该计划，将对七个HQP进行培训，以解决数据分析，预测和行动处方方面的定量问题解决和数据分析技能。加拿大雇主在物流和供应链，银行业，医疗保健和咨询等行业中非常寻求这些技能。