Location: Room SF3103, 3rd floor, Sandford Fleming Building, 10 King’s College Road, University of Toronto. MAP In this talk, we will give an introduction to modeling optimization problems where some parameters of the problem are uncertain and modeled as random variables. For instance, in power generation, energy demand is highly uncertain as well as renewal power supply at the […]
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 […]
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) […]
There is a growing market for crowd-shipping, which hires people to transport packages on their regular commutes, in the Greater Toronto Area (GTA). This thesis considers a hybrid crowd-shipping operation that hires crowd-shippers and regular drivers in a physical internet environment. An investigation into the spatial distribution of potential crowd-shippers is conducted by leveraging a […]
On-demand shared mobility is a promising and sustainable transportation approach that can mitigate vehicle externalities, such as traffic congestion and emission. On-demand shared mobility systems require matching of one (one-to-one) or multiple riders (many-to-one) to a vehicle based on real-time information. We propose a novel Graph-based Many-to-One ride-Matching (GMOMatch) algorithm for the dynamic many-to-one matching […]
Despite the plethora of tools and data available to transit planners, transit network design has remained mostly a manual task. Nevertheless, there have been many attempts to use algorithms and computing to optimise transit network design based on geography, demand and operating resources. However, the Transit Network Design Problem (TNDP) and Transit Network Design and […]
In this talk, we consider high-dimensional traffic signal control problems that arise in congested metropolitan areas. We focus on the use of high-resolution urban mobility stochastic simulators and formulate the control problems as high-dimensional continuous simulation-based optimization (SO) problems. We discuss the opportunities and challenges of designing SO algorithms for these problems. An important component in […]
