Abstract
This paper compares the application of the Monte Carlo simulation in incorporating travel time uncertainties in ambulance location problem using three models: Maximum Covering Location Problem (MCLP), Queuing Maximum Availability Location Problem (Q-MALP), and Multiserver Queuing Maximum Availability Location Problem (MQ-MALP). A heuristic method is developed to site the ambulances. The models are applied to the 33-node problem representing Austin, Texas, and the 55-node problem. For the 33-node problem, the results show that the servers are less spatially distributed in Q-MALP and MQ-MALP when the uncertainty of server availability is considered using either the independent or dependent travel time. On the other hand, for the 55-node problem, the spatial distribution of the servers obtained by locating a server to the highest hit node location is more dispersed in MCLP and Q-MALP. The implications of the new model for the ambulance services system design are discussed as well as the limitations of the modeling approach.
Highlights
In emergency medical services, a responsive and well-managed ambulance service is one of the key factors that can reduce fatality and suffering in patients
With travel time used as a proxy to the response time, we consider the application of the Monte Carlo approach to incorporating travel times uncertainty in the Maximum Covering Location Problem (MCLP), Queuing Maximum Availability Location Problem (Q-MALP), and Multiserver Queuing Maximum Availability Location Problem (MQ-MALP) models All three models are applied to the 33-node problem representing Austin, Texas, and the 55-node problem
This section considers the application of the Monte Carlo approach to incorporating travel times uncertainty in the MCLP, Q-MALP, and MQ-MALP models
Summary
A responsive and well-managed ambulance service is one of the key factors that can reduce fatality and suffering in patients. From the literature, some have considered using the travel time as a surrogate for response time in alleviating ambulance location problem [1, 2]. With travel time used as a proxy to the response time, we consider the application of the Monte Carlo approach to incorporating travel times uncertainty in the Maximum Covering Location Problem (MCLP), Queuing Maximum Availability Location Problem (Q-MALP), and Multiserver Queuing Maximum Availability Location Problem (MQ-MALP) models All three models are applied to the 33-node problem representing Austin, Texas, and the 55-node problem. A brief review of the MCLP, MALP, and the MQ-MALP models is provided This is followed by the Monte Carlo simulation of the MCLP, QMALP, and MQ-MALP with travel time uncertainty and the method used to site the ambulances.
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