Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok
Issued Date
2024-01-01
Resource Type
ISSN
21573611
eISSN
2157362X
Scopus ID
2-s2.0-85218042245
Journal Title
IEEE International Conference on Industrial Engineering and Engineering Management
Start Page
1099
End Page
1103
Rights Holder(s)
SCOPUS
Bibliographic Citation
IEEE International Conference on Industrial Engineering and Engineering Management (2024) , 1099-1103
Suggested Citation
Yongvongphaiboon K., Sirovetnukul R., Nilanont Y. Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok. IEEE International Conference on Industrial Engineering and Engineering Management (2024) , 1099-1103. 1103. doi:10.1109/IEEM62345.2024.10857036 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/105430
Title
Optimal Rendezvous Points of Mobile Stroke Units and Emergency Medical Services in the Thon Buri Side, Bangkok
Author(s)
Author's Affiliation
Corresponding Author(s)
Other Contributor(s)
Abstract
Acute ischemic stroke (AIS) requires rapid treatment to minimize neurological damage. Mobile Stroke Units (MSUs) provide timely interventions, and this study optimizes the rendezvous strategy (MSU-RS), where ambulances meet MSUs at predetermined points (rendezvous points). This research proposes a novel method to select optimal rendezvous points, reducing travel times, and enhancing MSU efficiency. Using a modified p-median problem and Geographic Information System (GIS) data, the research calculates precise travel times with the Open-Source Routing Machine (OSRM). A Genetic Algorithm (GA) is employed to solve this NP-hard problem. The research investigates the case study in central Bangkok incorporates telecommunication parameters critical for telemedicine. The result shows significant travel time reductions with the proposed GA configurations, especially the Mutation Dominant (MD) configuration. This research highlights the potential of GA in improving MSU rendezvous strategies, enhancing patient outcomes, and operational efficiency.