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Concept demonstrator: Holding site location, ambulance allocation, and relocation decision support tool
| Content Provider | Semantic Scholar |
|---|---|
| Author | Oosthuizen, A. C. |
| Copyright Year | 2017 |
| Abstract | Before the start of a shift, the dispatchers at the Western Cape Emergency Control Centre (WC ECC) decide where to place holding sites and how many ambulance to allocate to each holding site. During a shift they decide when and where to relocate ambulances. At present, dispatchers make these decisions based solely on their experience and intuition. In this project a concept demonstrator decision support tool (DST) is developed which produces solutions for the near-optimal placement of holding sites per shift, ambulance allocation, and relocation per hour of that shift based on predicted ambulance demand rates. The DST is developed with the aim of assisting the dispatchers at the WC ECC with holding site placement, ambulance allocation, and relocation decisions. The real-world instance utilised during the development of the concept demonstrator DST consists of six months’ historical call data from the City of Cape Town and the Cape Winelands municipalities. Singular spectrum analysis is used to forecast ambulance demand according to incident priority. The extended queuing maximum availability location problem model is adapted to fit the real-world instance. The model aims to simultaneously maximise expected ambulance coverage and minimise ambulance relocations by manipulating holding site placement, ambulance allocation, and relocation. The solution method implemented for the model as a whole is the artificial bee colony algorithm. The DST was solved for four planning week instances, at 95% service reliability. Predicted demand for the planning week is predicted using historical demand that precedes the planning week and a recommended schedule of holding site placement, ambulance allocation, and relocation is generated for the predicted ambulance demand. The performance of this schedule is evaluated using the observed historical demand for the planning week. iii Stellenbosch University https://scholar.sun.ac.za |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://scholar.sun.ac.za/bitstream/handle/10019.1/101310/oosthuizen_concept_2017.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
