MORA: A Multicriteria Optimal Resource Allocation and Decision Support Toolkit for Wildfire Management
Year: 2025
Type: article
Abstract: Forest ecosystems are vital to sustainable development, contributing to economic, environmental and social well-being. However, the increasing frequency and severity of wildfires threaten these ecosystems, demanding more effective and integrated fire management (IFM) strategies. Current suppression efforts face limitations due to high resource demands and the need for timely, informed decision-making under uncertain conditions. This paper presents the SILVANUS project’s approach to developing an advanced Decision Support System (DSS) designed to assist incident commanders in optimizing resource allocation during wildfire events. Leveraging Geographic Information Systems (GIS), real-time data collection, AI-enhanced analytics and multicriteria optimization algorithms, the SILVANUS DSS component integrates diverse data sources to support dynamic, risk-informed decisions. The system operates within a cloud-edge infrastructure to ensure scalability, interoperability and secure data management. We detail the formalization of the resource allocation problem, describe the implementation of the DSS within the SILVANUS platform, and evaluate its performance in both controlled simulations and real-world pilot scenarios. The results demonstrate the system’s potential to enhance situational awareness and improve the effectiveness of wildfire response operations.
Source: Algorithms
DOI: 10.3390/a18110677
Institution: University of West Attica
Language: English
Domain: Social Sciences
SDG: Life on land
Open Access status: gold
Estimated APC paid: $1,930
Funder: European Commission
OpenAlex ID: W4415489742
