A Biased VNS for the Covering Problem of the AED Locations
Author:
Affiliation:
1. Department of Industrial Management, King Mongkut's University of Technology North Bangkok, Thailand
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3638209.3638222
Reference18 articles.
1. Advanced reperfusion strategies for patients with out-of-hospital cardiac arrest and refractory ventricular fibrillation (ARREST): a phase 2, single centre, open-label, randomised controlled trial
2. Chung-Yuan Huang and Tzai-Hung Wen. 2014. Optimal installation locations for automated external defibrillators in Taipei 7-eleven stores: Using GIS and a genetic algorithm with a new stirring operator Computational and Mathematical Methods in Medicine 1–12.
3. Aaron Pulver Ran We A. Pulver Clay Mann. 2016. Locating AED Enabled Medical Drones to Enhance Cardiac Arrest Response Times. Prehosp Emerg Care. 2016. 378-389.
4. National coverage of out-of-hospital cardiac arrests using automated external defibrillator-equipped drones — A geographical information system analysis
5. Optimizing locations for the installation of automated external defibrillators (AEDs) in urban public streets through the use of spatial and temporal weighting schemes
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