Stepan Oskin MASc Thesis presentation by Stepan Oskin. Presented by the University of Toronto Institute of Transportation Engineers Student Chapter (UT-ITE).
This talk presents two projects that build data-driven solutions for city operations planning and management. The first part is devoted to the emerging food delivery operations. Working with a major food delivery service provider in China, we develop a data-driven optimization framework to minimize customers' expected delivery delay. To capture the driver's routing behaviors, we […]
The choice of vehicle type is one of the important logistics decisions made by firms. The complex nature of the choice process is due to the involvement of multiple agents. This study employs a random forest machine learning algorithm to represent these complex interactions with limited information about shipment transportation. The data are from commercial travel […]
Tri-POP is an online platform for operations of smart mobility solutions. In its core it combines online analytics for prediction, optimization, and personalization. It uses a bi-level optimization of system and user levels. The system optimization problem is solved periodically (e.g., every 5 minutes) to determine the optimal policy (e.g., pricing, fleet rebalancing, incentive allocation) […]
The point of travel forecasting is to inform decision-makers about the likely impacts of transport policies and investments that will irrevocably shape our cities and regions. In the past we've assumed that tomorrow will simply be a more crowded, prosperous, and congested version of our existing world. But today assuming a "business as usual" progression towards 20-30 […]
