Publicação
Optimization under uncertainty for forest fire containment
| Resumo: | Forest fires are a major problem that affects the entire world, causing tragic loss of life and serious injuries, which have been worsening due to global warming, making it essential to minimize the serious consequences of these phenomena. In this sense, this project addresses the problem of positioning resources to combat forest fires. As uncertainty is an important aspect in fire propagation modeling, stochastic approaches are used, such as the Equivalent Deterministic Model and the Sample Average Approximation. The purpose of these approaches is to determine the best locations to deploy a limited number of combat assets, for example fire crews. Another important point is to study how fire spreads in a forest given the region's topography, wind and other factors to incorporate fire propagation modeling with the management and planning of fire prevention and firefighting resources (optimization). Although there are several fire propagation simulation software, their integration with optimization problems is still very limited. In this work, this integration is achieved through the minimum travel time (MTT) principle that, when representing the forest by a network in which the transmission times between adjacent homogeneous forest zones are known, states the fire takes the quickest paths. This principle is used in mixed integer programming models to optimize the positioning of the available resources, both in a deterministic and in a stochastic setting. Computational experiments are conducted to validate the approach. |
|---|---|
| Autores principais: | Neto, David António Vieira dos Santos Moura |
| Assunto: | Forest fires Fire propagation modeling Planning of fire prevention and firefighting resources Optimization Incêndios florestais Modelação da propagação do fogo Gestão e planeamento dos recursos de prevenção e combate a incêndios Otimização |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | Forest fires are a major problem that affects the entire world, causing tragic loss of life and serious injuries, which have been worsening due to global warming, making it essential to minimize the serious consequences of these phenomena. In this sense, this project addresses the problem of positioning resources to combat forest fires. As uncertainty is an important aspect in fire propagation modeling, stochastic approaches are used, such as the Equivalent Deterministic Model and the Sample Average Approximation. The purpose of these approaches is to determine the best locations to deploy a limited number of combat assets, for example fire crews. Another important point is to study how fire spreads in a forest given the region's topography, wind and other factors to incorporate fire propagation modeling with the management and planning of fire prevention and firefighting resources (optimization). Although there are several fire propagation simulation software, their integration with optimization problems is still very limited. In this work, this integration is achieved through the minimum travel time (MTT) principle that, when representing the forest by a network in which the transmission times between adjacent homogeneous forest zones are known, states the fire takes the quickest paths. This principle is used in mixed integer programming models to optimize the positioning of the available resources, both in a deterministic and in a stochastic setting. Computational experiments are conducted to validate the approach. |
|---|