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2331. On a heuristic algorithm for optimal coordination of firefighting helicopters on large wildfires
Invited abstract in session MC-45: Methods and Algorithms of Decision Support, stream Decision Support Systems.
Monday, 12:30-14:00Room: 30 (building: 324)
Authors (first author is the speaker)
| 1. | Marta Rodríguez Barreiro
|
| Universidade da Coruña | |
| 2. | María José Ginzo Villamayor
|
| Universidad de Santiago de Compostela | |
| 3. | Fernando Pérez Porras
|
| Deapartamento de Ingeniería Gráfica y Geomática, Universidad de Córdoba | |
| 4. | Silvia Lorenzo-Freire
|
| University of A Coruña | |
| 5. | María Luisa Carpente Rodríguez
|
| Departamento de Matemáticas, Universidade da Coruña |
Abstract
This work presents a complete model for the optimal planning of helicopter operations during the extinguishing of a large wildfire. In large wildfires, many resources work together and must be coordinated in order to extinguish the wildfire in the shortest possible time while minimizing the damage caused. It is the responsibility of the fire coordinator to plan the work of these resources. To assist in this task, a model has been developed to find the optimal planning of helicopters in a firefighting situation. The model determines which aircraft should work on the fire and at what time. It also selects where the helicopters should load water and where they should rest. Using the level of efficiency associated with each area of the wildfire at each time, provided by the coordinator, the model also indicates at which points on the wildfire each helicopter will drop water. It also considers the fact that the aircraft work in groups, forming elliptical circuits that share water load and drop areas. It also takes into account Spanish aviation regulation. The model is presented in a time-extended graph, which allows the evolution of the wildfire to be reflected. The complexity of the model makes it impossible to solve it in a short time with the tested commercial solvers. Therefore, a heuristic based on the Simulated Annealing technique was implemented. The heuristic was tested with realistic data instances, achieving good results in a short time.
Keywords
- Disaster and Crisis Management
- Decision Support Systems
- Algorithms
Status: accepted
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