Work

Designing a clustering algorithm for optimizing health station locations

Year: 2025

Type: article

Abstract: In this paper, we define the optimization of health station locations as a clustering problem. We design a robust algorithm for the problem using a pre-calculated overhead graph for fast distance calculations and apply a robust clustering algorithm called random swap to provide accurate optimization results. We study the effect of three cost functions (Euclidean distance, squared Euclidean distance, travel cost) using real patient locations in North Karelia, Finland. We compare the optimization results with the existing health station locations. We found that the algorithm optimized the locations beyond administrative borders and strongly utilized the transport network. The results can provide additional insight for the decision-makers.

Source: International Journal of Health Geographics

DOI: 10.1186/s12942-025-00390-1

Authors: Pasi Fränti, Sami Sieranoja, Tiina Laatikainen

Institution: University of Eastern Finland

Language: English

Topic: Facility Location and Emergency Management

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure, Good health and well-being

Open Access status: gold

Estimated APC paid: $3,290