Speaker
Description
This work addresses the design of networks to support wildfire preparedness activities, namely surveillance, detection, and suppression. The problem is defined over a graph where nodes represent potential locations for positioning resources (e.g., watchtowers or firefighting crews), and arcs denote direct connections (e.g., roads) between these locations.
We propose a mixed-integer programming model that integrates two decision layers: covering (selecting resource positions to ensure area coverage) and network design (selecting arcs to define the network structure). The model supports different topological configurations, including spanning trees, shortest-path trees, and Hamiltonian circuits. Different objectives are considered, such as maximizing coverage and minimizing the total network length.
Computational experiments are conducted on a real-world landscape to evaluate the performance and flexibility of the proposed approach. The results highlight the trade-offs between coverage and network compactness and show how the model can adapt to different planning priorities and operational constraints.
This integrated formulation offers a general and extensible framework for designing spatially distributed wildfire preparedness systems, with potential applicability to other emergency response planning contexts.
