ISyE Graduate Seminar: Data-driven Greedy Policies and Information-Relaxation Bounds for Ambulance Location and Deployment
Please join us for our next seminar of fall semester. This cross-track seminar will feature Professor Lavanya Marla from the University of Illinois at Urbana-Champaign who will discuss data-driven greedy policies and information-relaxation bounds for ambulance location and deployment.
Livestreaming: Again this year we are coordinating with the Institute for Mathematics and its Applications to livestream our seminars on the IMA YouTube Channel. Attend in person or watch the livestream
3:15 p.m. - Refreshments
3:30 p.m. - Graduate Seminar
Professor Lavanya Marla
Industrial and Enterprise Systems Engineering
University of Illinois at Urbana-Champaign
About the seminar
Marla and her colleagues present an efficient data-driven computational solution and bounding approach for static allocation of an ambulance fleet and its dynamic redeployment. The goal is to position (or re-position) ambulances to bases to maximize the system's service level. Central to their approach is a discrete-event simulator to evaluate the impact of ambulance deployments to logs of emergency requests.
Marla and her team first model ambulance allocation as an approximately-submodular-maximization problem, and devise a simple and efficient greedy algorithm that produces both static allocations and dynamic repositioning policies. In parallel, they find data-driven information-relaxation bounds for both static and dynamic cases. They build even tighter information-relaxation bounds by penalizing the previous relaxations. Marla’s approach allows the computation of tight bounds without incurring the curse of dimensionality common to such approaches.
About the Speaker
The bounding methods help inform policymakers about the viability of proposed fleet sizes and policies being adopted by the contracted EMS agencies. Their computational experiments on an Asian city's EMS demonstrate the tractability and efficiency of their greedy algorithm and bounding methods. The first part of this work is with Ramayya Krishnan and Yisong Yue, and the latter part with Achal Bassamboo.
Lavanya Marla is an assistant professor in the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign. Prior to her current position, she was a systems scientist with the Heinz College at Carnegie Mellon University. She earned her Ph.D. in Transportation Systems from the Massachusetts Institute of Technology and bachelor’s degree from the Indian Institute of Technology Madras. Her research interests are in robust and dynamic decision-making under uncertainty and game theoretic analysis for large-scale transportation and logistics systems, combining tools from data-driven optimization, statistics, simulation, and machine learning.
Marla’s research is funded by an integrative National Science Foundation grant, a Department of Homeland Security cyber-security grant, the Department of Transportation, the US-India Educational Foundation, the INFORMS Transportation and Logistics Society, and aviation companies. Her work has received an honorable mention for the Anna Valicek award from AGIFORS, a best presentation award from AGIFORS, a KDD Startup Research award, and a Top-10 cited paper recognition from Transportation Research Part A: Policy and Practice.