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Timely emergency medical response in rural regions depends on efficient road-network connectivity between geographically dispersed habitations and health-care facilities.
This research presents a graph-theoretic spatial optimization framework for multi-stop ambulance patrol routing in Guntur District, Andhra Pradesh, India.
The proposed framework models healthcare facilities and habita-tion clusters as a weighted graph and formulates ambulance routing as a localized Traveling Salesman Problem (TSP) integrated with Vehicle Routing Problem (VRP) principles.
The system incorporates Community Health Centres (CHCs), Primary Health Centres (PHCs), Sub-Centres, rural habitations, and road-network datasets within an interactive Geographic Information System (GIS) environment.
Using shortest-path computation, closed-loop ambulance patrol circuit generation, and alternative route optimization, the framework supports efficient emergency healthcare accessibility across rural regions.
A web-based implementation developed using React, Vite, Leaflet GIS, Node.js, and Prisma ORM enables real-time healthcare map visualization, PHC-wise route generation, and dynamic ambulance patrol monitoring.
Experimental eval-uation conducted on graph sizes ranging from 100 to 300 nodes assessed execution latency, memory utilization, and routing efficiency.
Results demonstrate that the proposed framework produces near-optimal ambu-lance patrol routes while maintaining scalable computational performance under increasing graph density.
The integration of graph-theoretic optimization with interactive GIS visualization provides an efficient, scalable, and adaptive decision-support framework for rural emergency healthcare logistics, ambulance routing, and healthcare accessibility planning.
"Graph-Theoretic Spatial Optimization for Multi-Stop Ambulance Routing Using a Localized Traveling Salesman Problem in Rural Healthcare Networks", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a882-a903, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606092.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator