Optimal allocation of defibrillator drones in mountainous regions

Christian Wankmüller*, Christian Truden, Christopher Korzen, Philipp Hungerländer, Ewald Kolesnik, Gerald Reiner

*Corresponding author for this work

Publication: Scientific journalJournal articlepeer-review

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Abstract

Responding to emergencies in Alpine terrain is quite challenging as air ambulances and mountain rescue services are often confronted with logistics challenges and adverse weather conditions that extend the response times required to provide life-saving support. Among other medical emergencies, sudden cardiac arrest (SCA) is the most time-sensitive event that requires the quick provision of medical treatment including cardiopulmonary resuscitation and electric shocks by automated external defibrillators (AED). An emerging technology called unmanned aerial vehicles (or drones) is regarded to support mountain rescuers in overcoming the time criticality of these emergencies by reducing the time span between SCA and early defibrillation. A drone that is equipped with a portable AED can fly from a base station to the patient’s site where a bystander receives it and starts treatment. This paper considers such a response system and proposes an integer linear program to determine the optimal allocation of drone base stations in a given geographical region. In detail, the developed model follows the objectives to minimize the number of used drones and to minimize the average travel times of defibrillator drones responding to SCA patients. In an example of application, under consideration of historical helicopter response times, the authors test the developed model and demonstrate the capability of drones to speed up the delivery of AEDs to SCA patients. Results indicate that time spans between SCA and early defibrillation can be reduced by the optimal allocation of drone base stations in a given geographical region, thus increasing the survival rate of SCA patients.

Original languageEnglish
Pages (from-to)785-814
Number of pages30
JournalOR Spectrum
Volume42
Issue number3
DOIs
Publication statusPublished - 1 Sept 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102009 Computer simulation
  • 502052 Business administration
  • 502012 Industrial management
  • 211
  • 502017 Logistics
  • 502032 Quality management

Keywords

  • Automated external defibrillator
  • Drone
  • Emergency response
  • Integer linear programming
  • Location allocation
  • Sudden cardiac arrest

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