Algorithms for Societal Networks

Societal Networks are the engineering subsystems underlying the operation of cities; for example, transportation networks, energy grids, water delivery and waste management networks.  Mass urbanization is straining these networks and, as demand exceeds the supply, a significant performance degradation or failure is becoming the norm. To combat this  trend, operators of these networks (cities, businesses) are deploying low-cost, sensors (i) to ensure the safe and reliable operation of the networks, and (ii) to dynamically deploy resources to serve the demand. 

 

In this talk, we describe some key algorithmic challenges arising in transportation networks.  We consider example problems in three main categories: (1) real-time inference and decision-making, (2) “nudge” algorithms (algorithms that nudge the demand in real-time to adapt to the supply), and (3) matching algorithms.  The examples highlight algorithmic, modeling and deployment challenges in applications such as taxi/ride-sharing services, public transit systems, and e-commerce and delivery networks.