Name
Abstract | ||
|---|---|---|
Emergency Medical Service (EMS) systems operate under the pressure of knowing that human lives might be directly at stake. In the public eye there is a natural expectation of efficient response. There is abundant literature on the topic of efficient planning of EMS systems (maximizing expected coverage or minimizing response time). Other objectives have been considered but the literature available is very sparse compared to efficiency-based works. Furthermore, while real size EMS systems have been studied, the use of exact models is usually hindered by the amount of computational time required to obtain solutions. We approach the planning of large-scale EMS systems including fairness considerations using a Tabu Search-based heuristic with an embedded approximation procedure for the queuing submodel. This allows for the analysis of large-scale real systems, extending the approach in which strategic decisions (location) and operative decisions (dispatching) are combined to balance efficiency and fairness. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1057/jors.2014.83 | Journal of the Operational Research Society |
Keywords | Field | DocType |
location/allocation in healthcare,hypercube model,tabu search | Heuristic,Computer science,Operations research,Response time,Queueing theory,Real systems,Tabu search,Operations management | Journal |
Volume | Issue | ISSN |
66 | 7 | 0160-5682 |
Citations | PageRank | References |
6 | 0.43 | 32 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hector Toro-DíAz | 1 | 38 | 1.44 |
| Maria E. Mayorga | 2 | 107 | 11.08 |
| Laura A. Mclay | 3 | 192 | 15.16 |
| Hari K. Rajagopalan | 4 | 117 | 8.33 |
| Cem Saydam | 5 | 161 | 8.55 |