Speaker: Supriyo Ghosh

Date and Venue: Tuesday, 19th September 4 pm, SIT 001.

Title:Proactive Resource Redistribution for Improving Efficiency of Urban Environments

Abstract: TDue to the increasing population and lack of coordination, there is a mismatch in supply and demand of common resources (e.g., shared bikes, ambulances, taxis) in urban environments, which has deteriorated a wide variety of quality of life metrics such as success rate in issuing shared bikes, response times for emergency needs, waiting times in queues etc. Thus, I will talk about efficient algorithms that optimise the quality of life metrics by proactively redistributing the resources using intelligent operational (day-to-day) and strategic (long-term) decisions in the context of urban transportation and health & safety. For urban transportation, I will explain three operational decision making approaches for Bike Sharing System (BSS), to reduce the loss in customer demand which is caused due to the mismatch of supply and demand for bikes at base stations: (a) Dynamic repositioning of bikes using carrier vehicles by considering the expected demand for multiple time-steps, which is suitable for BSS with consistent demand patterns. In addition, I will describe decomposition and abstraction mechanisms to speed up the solution process; (b) Robust redistribution of bikes using the notion of two-player adversarial game to address the scenarios where the demand has high variance; and (c) A self-sufficient and green mode of bike repositioning using bike-trailers, where an incentivization mechanism is used to crowdsource the repositioning tasks among customers within a central budget constraint. For health & safety, I will briefly describe a strategic decision making approach for Emergency Medical Service (EMS). The goal is to place base stations at “right” location and allocate “right” number of ambulances on those bases, so that the response times for emergency needs are minimized. I will explain an accelerated version of greedy algorithm on top of a data-driven optimisation formulation to jointly consider the placement of bases and allocation of ambulances. Finally, I will conclude with possible future directions and the potential of proactive resource redistribution in building smart and sustainable cities.

Speaker Bio: Supriyo GHOSH is a PhD student in Information Systems at Singapore Management University (SMU), specializing in Intelligent Systems & Optimisation. His research interests include mathematical optimization, data-driven modelling, intelligent decision analytics, automated planning & scheduling and machine learning. He has published papers at prestigious AI journals (e.g., JAIR) and conferences (e.g., IJCAI, ICAPS).