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Approximate Dynamic Programming for Ambulance Redeployment

School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Center for Applied Mathematics, Cornell University, Ithaca, New York 14853
School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
msm57{at}cornell.edu
mr324{at}cornell.edu
sgh9{at}cornell.edu
ht88{at}cornell.edu

We present an approximate dynamic programming approach for making ambulance redeployment decisions in an emergency medical service system. The primary decision is where we should redeploy idle ambulances so as to maximize the number of calls reached within a delay threshold. We begin by formulating this problem as a dynamic program. To deal with the high-dimensional and uncountable state space in the dynamic program, we construct approximations to the value function that are parameterized by a small number of parameters. We tune the parameters using simulated cost trajectories of the system. Computational experiments demonstrate the performance of the approach on emergency medical service systems in two metropolitan areas. We report practically significant improvements in performance relative to benchmark static policies.

Key words: approximate dynamic programming; simulation; Markov decision processes
History: received April 2008; revised March 2009; accepted May 2009.