 Multi-drone rescue search in a large networkVictor Gonzalez and Patrick Jaillet European Journal of Operational Research, 2025, vol. 324, issue 3, 787-798 Abstract: Natural disasters are recurring emergencies that can result in numerous deaths and injuries. When a natural disaster occurs, rescue teams can be sent to help affected survivors, but deploying them efficiently is a challenge. Rescuers not knowing where affected survivors are located poses a significant challenge in delivering aid. With the development of new technologies, there are new possibilities to reduce this uncertainty, alleviating this challenge. One can first send out automated drones to locate affected survivors and then send rescue teams to their locations. We develop a model for the search process and construct mathematical methods to construct efficient search routes. We utilize a divide and conquer technique to determine the routes that are most likely to yield an efficient search. We combine this with our mathematical methods to construct efficient search routes in real-time and a method to update these routes in real-time as drones gather information. Keywords: Nonlinear programming; Large-scale optimization; Routing; Networks (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:324:y:2025:i:3:p:787-798 DOI: 10.1016/j.ejor.2025.02.003 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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