Equity Constrained Dispatching Model of Emergency Medical Services (1.0.0)
Agent-based modeling and simulation was used to evaluate two different ambulance dispatching policies in equity constrained emergency medical services: first, a policy based on maximum reward and second, a policy based on the Markov Decision Process formulation. Four equity constraints were used: two from the patients’ side and two from the providers’ side.The call for services will arrive from different call locations and the ambulances are base located at multiple location. The paper extends the work by McLay and Mayorga (2013a, 2013b) using agent-based modeling and simulation approach .
Release Notes
The existing model implements two dispatching policies:
- a policy based on nearest ambulance (maximum reward algorithm)
- a policy based on the Markov Decision Process formulation which is solved using value iteration.
Associated Publications
Sreekanth V.K., Ram Babu Roy, (2017) “Equity-constrained dispatching models for emergency medical services”, Team Performance Management: An International Journal, Vol. 23 Issue: 1/2, pp.28-45, doi: 10.1108/TPM-10-2015-0051 Permanent link to this document: http://dx.doi.org/10.1108/TPM-10-2015-0051
This release is out-of-date. The latest version is
1.2.0
Equity Constrained Dispatching Model of Emergency Medical Services 1.0.0
Submitted by
Sreekanth V K
Published Sep 08, 2016
Last modified Feb 23, 2018
Agent-based modeling and simulation was used to evaluate two different ambulance dispatching policies in equity constrained emergency medical services: first, a policy based on maximum reward and second, a policy based on the Markov Decision Process formulation. Four equity constraints were used: two from the patients’ side and two from the providers’ side.The call for services will arrive from different call locations and the ambulances are base located at multiple location. The paper extends the work by McLay and Mayorga (2013a, 2013b) using agent-based modeling and simulation approach .
Release Notes
The existing model implements two dispatching policies:
- a policy based on nearest ambulance (maximum reward algorithm)
- a policy based on the Markov Decision Process formulation which is solved using value iteration.
