Abstract: Patient survival from out-of-hospital cardiac arrest (OHCA) can be improved by augmenting traditional ambulance response with the dispatch of community first responders (volunteers) who are alerted via an app. How many volunteers are needed and from where should volunteers be recruited? We use a combination of Poisson point process modeling and finite-dimensional convex optimization to address these questions. Having volunteer density in proportion to OHCA probability density is not optimal, though it is very good. Moreover, the right areas from which to recruit are not always obvious, because volunteers recruited from one area may spend time in various areas across a city.
We discretized the optimization problem for simplicity and tractability, but is that necessary? In the second part of the talk I’ll describe work developing a Frank-Wolfe style algorithm for solving an infinite-dimensional version of a certain convex optimization problem. The resulting algorithm is readily implementable and enjoys strong convergence properties.
I’ll present results for both stylized problems and for a case study of the city of Auckland, New Zealand.
This is joint work with Pieter van den Berg, Caroline Jagtenberg, Hemeng (Maggie) Li, Raghu Pasupathy and Di Yu
Bio: Professor Shane G. Henderson holds the Charles W. Lake, Jr. Chair in Productivity in the School of Operations Research and Information Engineering (ORIE) at Cornell University. His research interests include discrete-event simulation, simulation optimization, emergency services planning and transportation. He is an INFORMS Fellow and a co-recipient of the INFORMS Wagner Prize for his work on bike-sharing programs. He likes climbing walls, bicycles, Harry Potter and being a Dad.