Ontology-Driven Multicriteria Decision Support for Victim Evacuation

Linda Elmhadhbi, Mohamed-Hedi Karray (), Bernard Archimè de (), J. Neil Otte () and Barry Smith ()
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Linda Elmhadhbi: University of Toulouse, INP-ENIT, Tarbes 65000, France
Mohamed-Hedi Karray: University of Toulouse, INP-ENIT, Tarbes 65000, France
Bernard Archimè de: University of Toulouse, INP-ENIT, Tarbes 65000, France
J. Neil Otte: Johns Hopkins University Applied, Physics Laboratory, Laurel, Maryland 20707, USA
Barry Smith: University at Buffalo, New York 14203, USA

International Journal of Information Technology & Decision Making (IJITDM), 2022, vol. 21, issue 01, 243-272

Abstract: In light of the complexity of unfolding disasters, the diversity of rapidly evolving events, the enormous amount of generated information, and the huge pool of casualties, emergency responders (ERs) may be overwhelmed and in consequence poor decisions may be made. In fact, the possibility of transporting the wounded victims to one of several hospitals and the dynamic changes in healthcare resource availability make the decision process more complex. To tackle this problem, we propose a multicriteria decision support service, based on the Analytic Hierarchy Process (AHP) method, that aims to avoid overcrowding and outpacing the capacity of a hospital to effectively provide the best care to victims by finding out the most appropriate hospital that meets the victims’ needs. The proposed approach searches for the most appropriate healthcare institution that can effectively deal with the victims’ needs by considering the availability of the needed resources in the hospital, the victim’s wait time to receive the healthcare, and the transfer time that represents the hospital proximity to the disaster site. The evaluation and validation results showed that the assignment of hospitals was done successfully considering the needs of each victim and without overwhelming any single hospital.

Keywords: Multicriteria decision support; ontology; victims’ evacuation; disaster response (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S021962202150053X

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