Location Planning of Emergency Medical Facilities Using the p-Dispersed-Median Modeling Approach
Bibliographic Data
| ID | 22034767 |
|---|---|
| Authors | Christie Oh (0000-0002-1682-1802, University of Tennessee at Knoxville), Yongwan Chun (0000-0002-4957-1379, The University of Texas at Dallas), Hyun Kim (0000-0002-7637-678X, University of Tennessee at Knoxville, corresponding author) |
| Year | 2023 |
| Volume | 12 |
| Issue | 12 |
| Pages | 497 |
| Publication date | 2023-12-12 |
| 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/ijgi12120497 |
| OpenAlex | W4389614249 |
| Language | EN |
| Citations received | 2 |
| References cited | 39 |
This research employs a spatial optimization approach customized for addressing equitable emergency medical facility location problems through the p-dispersed-median problem (p-DIME). The p-DIME integrates two conflicting classes of spatial optimization problems, dispersion and median problems, aiming to identify the optimal locations for emergency medical facilities to achieve an equitable spatial distribution of emergency medical services (EMS) while effectively serving demand. To demonstrate the utility of the p-DIME model, we selected Gyeongsangbuk-do in South Korea, recognized as one of the most challenging areas for providing EMS to the elderly population (aged 65 and over). This challenge arises from the significant spatial disparity in the distribution of emergency medical facilities. The results of the model assessment gauge the spatial disparity of EMS, provide significantly enhanced solutions for a more equitable EMS distribution in terms of service coverage, and offer policy implications for future EMS location planning. In addition, to address the computational challenges posed by p-DIME’s inherent complexity, involving mixed-integer programming, this study introduces a solution technique through constraint formulations aimed at tightening the lower bounds of the problem’s solution space. The computational results confirm the effectiveness of this approach in ensuring reliable computational performance, with significant reductions in solution times, while still producing optimal solutions
Algorithm · Business · Facility location problem · Integer programming · Linear programming · Mathematical optimization · Medical emergency · Operations research · Population · Computer Science · Engineering · Facility Location and Emergency Management · Mathematics · Medicine · Urban Transport and Accessibility · Vehicle Routing Optimization Methods · Emergency Medical Services
Central Facilities Location
Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph
The Location of Emergency Service Facilities
Assessing Trauma Center Accessibility for Healthcare Equity Using an Anti-Covering Approach
Measuring spatial accessibility to healthcare for populations with multiple transportation modes
The Maximal Covering Location Problem
Locating healthcare facilities using a network-based covering location problem
| Citations per year | 2 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |