Optimization of ambulance location model using maximal coverage location problem and gradual coverage location problem

Abstract

Emergency Medical Services (EMS) in Malaysia was categorized as underdeveloped emergency care system in 1990s. This was due to the lack of specialty in emergency medical systems and academic activities. By 2007, EMS in Malaysia has been significantly improved and is categorized as in developing phase. In October 2007, Malaysia Emergency Response Services 999 was introduced to combine several emergency service numbers as one emergency number 999. However, Malaysia is still lack of academic contribution in EMS optimization research. One of the ways to improve the efficiency of EMS delivery is the application of ambulance location model. The ambulance location model is used to find the best locations to place ambulances. In this research, a grid map based on Johor Bahru population is created. Euclidean distance is used as distance measurement in the map. Two ambulance location models, Maximal Coverage Location Problem (MCLP) and Gradual Coverage Location Problem (GCLP) are developed, and strategic ambulance location sites in the developed map are solved using Particle Swarm Optimization algorithm. The performances of both models are then measured using the developed simulator by analyzing ambulance response time, simulation coverage, total travel distance and ambulance preparedness. Different settings including current Johor Bahru EMS settings are simulated using the simulator. By using the simulator, advantages and disadvantages of different models are successfully addressed. Simulation results show that EMS setting in Johor Bahru is the least optimized and in most cases, GCLP is better than MCLP. For the deployment of 7 ambulances at 10 km coverage radius, the ambulance response time for setting GCLP is 5.5 minutes, which is lower than setting MCLP (7.4 minutes), and setting hospital (7.02 minutes).