Grant: Discovery Grants Program - Individual

Sustainability is nowadays a paramount global concern. In the transportation sector, institutions are increasingly adopting electric vehicles (EVs) due to their direct impact on reducing emissions. The past decade has thus seen significant growth in the use of EVs in logistics networks, particularly for last-mile deliveries (deliveries from consolidation hubs to final destinations). In Canada, Canada Post has committed to electrifying its fleet of 14,000 delivery vehicles by 2040. Purolator is investing $1 billion to electrify its Canadian delivery fleet. As such, EVs will have a significant role in the Canadian economy and the country's goal of net zero emissions by 2050. Several advances have been made in recent years to optimize EV last-mile delivery networks. Nevertheless, substantial challenges persist. Operating an efficient logistics network involves coordinating strategic, tactical, and operational decisions to ensure sustainability, resilience, and cost-effectiveness. However, most research on EV last-mile logistics has focused on optimizing the operational aspects, such as battery charging, routing, and delivery schedules, while strategic and tactical decisions, such as capacity planning, fleet composition, and distribution zone design, are assumed to be fixed. In reality, companies are in the process of replacing highly optimized networks that are based on traditional vehicles with EVs. The substantial investments dedicated to EV adoption thus underscore the significance of these strategic and tactical problems. This research program aims to investigate timely optimization models for the strategic and tactical planning of EV adoption in logistics networks. At the strategic level, the research will focus on optimizing network sizing, capacity planning, and fleet composition. These strategic decisions are made under substantial uncertainty on future network demand and operational capabilities. This research program will thus develop new models for the strategic design of EV last-mile networks under uncertainty and design custom solution methods for these models. On the tactical side, the adoption of EVs is a gradual process, and EVs will coexist with traditional vehicles for several years. For example, Amazon aims to have 100,000 delivery EVs on the road by 2030, with full EV adoption by 2040. This research program will thus investigate optimization models for the phased adoption and integration of EVs into existing networks. The outcomes of this program will bring research capabilities, financial benefits, service quality, and network resiliency for logistics companies and environmental and sustainability benefits for society. Overall, this research program will make theoretical and practical contributions to various areas of operations research, including large-scale mixed-integer programming, robust and stochastic programming, and the development of new models and solution methods for sustainable transportation networks.