Grant: Canada Research Chairs

Modern economies are now globalized and operate via the access to supply chains that support trade at all geographical levels. Transportation and logistics systems are the backbone of supply chains. To operate, supply chains need to access efficient transportation and logistics services to move freight from origins to destinations within the desired delays while minimizing the overall costs. Transportation and logistics systems are thus one of the main levers that enable national economies to grow and for cities to thrive. At the same time, the transportation sector is one of the main sources of greenhouse gas emissions. The management of transportation and logistics systems thus defines an important paradox. On the one hand, transportation and logistics services are paramount to reach the country's societal and economic objectives, but on the other hand, they pose important environmental challenges that considerably complicate the country's overall efforts to combat climate change. Furthermore, transportation and logistics systems are planned and operated in highly uncertain environments where the contextual information randomly varies. In such decision-making contexts, not accounting for the contextual uncertainty directly leads to arbitrarily bad plans that will not achieve the system’s goals. The Chair will thus develop novel stochastic optimization methods (which use probability distributions to account for how uncertain parameters can randomly vary) that can efficiently solve the main planning problems that are relevant for modern transportation and logistics systems. Specifically, the chair will first study general systems with challenging characteristics: a) multimodal (i.e., that entail multiple transportation modes) evolving towards synchromodal systems (i.e., that rely on higher levels of coordination, cooperation and synchronization between the stakeholders), that are b) consolidation-based (e.g., less-than-truckload or package delivery cases) and c) used for different purposes (e.g., long-haul freight transportation, city logistics and humanitarian logistics). Second, it will propose novel stochastic optimization methodologies to efficiently solve the main planning problems for such systems. Emphasis will be placed on designing methodologies that solve the problems while considering both the foreseeable uncertainty (e.g., seasonal demand variations) and the disruptive events that affect the system's performance (e.g., service failures).