A simulation optimization framework for ambulance deployment and relocation problems

• This paper studies ambulance deployment and relocation problems.
• This paper proposes a simulation optimization method for the problem.
• An example about its application in Shanghai is given.
• Some managerial implications are obtained from numerical experiments.

This paper studies ambulance deployment and relocation problems, which are two of the core decisions faced by emergency medical service control centers in metropolis. The challenge in the problems is to estimate the operational performance of a deployment plan under stochastic environments. More specifically, the stochastic and dynamic nature of request arrivals, fulfillment processes, and complex traffic conditions as well as the time-dependent spatial patterns of some parameters complicate the decisions in the problems. This paper proposes a simulation optimization method that enables evaluating the operational performance of deployment plans through a detailed simulation model. For guiding the search process in the simulation optimization method, the genetic algorithm is employed in this study. On the basis of the deployment decisions, a mathematical model on ambulance relocation is also proposed for adapting to the dynamic changing environments along the time. To illustrate the proposed method’s usage in practice, a demo example about its application in Shanghai is given. Some numerical experiments are also performed to validate the effectiveness and the efficiency of the proposed methods.