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Optimisation of Disaster Resource Distribution with Risk Uncertainty Using Fuzzy Theory

Perez-Palacin, Diego 1; Johnson, Kenneth; Grassi, Vincenzo; Mirandola, Raffaela 1
1 Institut für Informationssicherheit und Verlässlichkeit (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract:

Disasters are unexpected events that can cause widespread disruption of an urban region. Disaster managers are tasked with distributing lifesaving resources to meet evolving demand in the immediate aftermath of a disaster. However, decision-making during the first response is often characterised by a lack of information on current road conditions, and thus, the travel risk posed to teams remains uncertain. This paper presents a decision-making framework underpinned by Markov decision processes to verify provably correct team resource distribution strategies satisfying temporal logic constraints under travel risk vagueness. We implement the framework to express vagueness using fuzzy logic and demonstrate its effectiveness across a range of disaster resourcing scenarios.


Verlagsausgabe §
DOI: 10.5445/IR/1000196031
Veröffentlicht am 07.08.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 12.04.2026
Sprache Englisch
Identifikator ISBN: 979-8-4007-2478-7
KITopen-ID: 1000196031
Erschienen in Proceedings of the IEEE/ACM 14th International Conference on Formal Methods in Software Engineering
Veranstaltung 14th International Conference on Formal Methods in Software Engineering (FormaliSE 2026), Rio de Janeiro, Brasilien, 12.04.2026 – 13.04.2026
Verlag Association for Computing Machinery (ACM)
Seiten 46 - 56
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