Ambulances Deployment Problems
Categorization, Evolution and Dynamic Problems Review
Bibliographic Data
| ID | 22034337 |
|---|---|
| Authors | Dionicio Neira‐Rodado (0000-0003-0837-7083, University of the Coast, corresponding author), Dionicio Neira-Rodado (University of the Coast), John Willmer Escobar (0000-0001-6175-9553, Universidad del Valle), Sally McClean (0000-0002-6871-3504, University of Ulster) |
| Year | 2022 |
| Volume | 11 |
| Issue | 2 |
| Pages | 109 |
| Publication date | 2022-02-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi11020109 |
| OpenAlex | W4210756468 |
| Language | EN |
| Citations received | 3 |
| References cited | 141 |
In this paper, an analytic review of the recent methodologies tackling the problem of dynamic allocation of ambulances was carried out. Considering that state-of-the-art is moving to deal with more extensive and dynamic problems to address in a better way real-life instances, this research looks to identify the evolution and recent applications of this kind of problem once the basic models are explored. This extensive review allowed us to identify the most recent developments in this problem and the most critical gaps to be addressed. In this sense, it is essential to point out that the dynamic location of emergency medical services (EMS) is nowadays a relevant topic considering its impact on the healthcare system outcomes. Issues related to forecasting, simulation, heterogeneous fleets, robustness, and solution speed for real-life problems, stand out in the identified gaps. Applications of machine learning the deployment challenges during epidemic outbreaks such as SARS and COVID-19 were also explored. At the same time, a proposed notation tries to tackle the fact that the word problem in this kind of work refers to a model on many occasions. The proposed notation eases the comparison between the different model proposals found in the literature
Categorization · Data science · Management science · Notation · Operations research · Software deployment · Software engineering · Computer Science · Engineering · Evacuation and Crowd Dynamics · Facility Location and Emergency Management · Vehicle Routing Optimization Methods · Artificial Intelligence
Mode of questionnaire administration can have serious effects on data quality
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The Location of Emergency Service Facilities
Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus
Dynamic Floating Stations Model for Emergency Medical Services with a Consideration of Traffic Data
Generalized Coverage Models and Public Facility Location
Optimal location under time or distance constraints
The Maximal Covering Location Problem
Generating a spatial coverage plan for the emergency medical service on a regional scale
Geography in Coverage Modeling
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |