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.

Perez-Palacin, D., Johnson, K., Grassi, V., Mirandola, R. (2026). Optimisation of Disaster Resource Distribution with Risk Uncertainty Using Fuzzy Theory. In Proceedings - 2026 IEEE/ACM 14th International Conference on Formal Methods in Software Engineering, FormaliSE 2026 (pp.46-56). Association for Computing Machinery, Inc [10.1145/3793656.3793691].

Optimisation of Disaster Resource Distribution with Risk Uncertainty Using Fuzzy Theory

Grassi, Vincenzo;
2026-01-01

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.
14th International Conference on Formal Methods in Software Engineering, FormaliSE 2026
Windsor Barra Hotel, bra
2026
SIGSOFT
Rilevanza internazionale
2026
Settore IINF-05/A - Sistemi di elaborazione delle informazioni
English
decision-making; fuzzy logic; disaster management
Intervento a convegno
Perez-Palacin, D., Johnson, K., Grassi, V., Mirandola, R. (2026). Optimisation of Disaster Resource Distribution with Risk Uncertainty Using Fuzzy Theory. In Proceedings - 2026 IEEE/ACM 14th International Conference on Formal Methods in Software Engineering, FormaliSE 2026 (pp.46-56). Association for Computing Machinery, Inc [10.1145/3793656.3793691].
Perez-Palacin, D; Johnson, K; Grassi, V; Mirandola, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/474963
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