Emergency ambulance deployment in Barbados: a multi-objective approach

• Published in: The Journal of the Operational Research Society Vol. 53; no. 2; pp. 185 - 192
• Main Author: Harewood, S I
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.02.2002; Palgrave Macmillan Press; Palgrave Macmillan UK; Palgrave; Taylor & Francis Ltd
• Subjects: Ambulance services; Ambulances; Applied sciences; Average speed; Business and Management; Case-oriented Paper; Case-Oriented Papers; developing countries; Exact sciences and technology; Flows in networks. Combinatorial problems; health service; Health services; location; Management; Mathematical models; Modeling; Objective functions; Operational research and scientific management; Operational research. Management science; Operations research; Operations Research/Decision Theory; Probabilistic modeling; Queuing; Roads; Simulations; Studies; Traffic volume; Travel time; health service; developing countries; location; Availability; Performance evaluation; Data analysis; Medical transport; Multiobjective programming; Unfolding; Developing countries; Location problem; Optimization; Ambulance; Relaxation method; Emergency; Reliability; Data gathering
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/palgrave.jors.2601250

A multi-objective version of the Maximum Availability Location Problem is presented in this paper. The assumption of server independence is relaxed by adopting the approach of the Queuing Probabilistic Location Set Covering Problem for calculating the probability that all servers in a given region are busy. The first objective seeks to maximize the population receiving coverage within a given distance standard and with a given level of reliability. The second objective chooses those locations which minimize the cost of covering the population. This model is used to obtain sets of good locations using data obtained from the Barbados Emergency Ambulance Service. The solutions obtained from the optimization model are then subject to a detailed analysis by simulation. The results reveal the potentially good performance of the system, when locations derived from the optimization model are used.