A Simulation-Based Optimization Approach to the Firefighting Resource Scheduling Problem

被引：0

作者：

Paiva, Emerson J. ^{[1
,2
]}

Matos, Marina A. ^{[1
]}

Rocha, Ana Maria A. C. ^{[1
]}

机构：

[1] Univ Minho, ALGORITMI Res Ctr LASI, Campus Gualtar, P-4710057 Braga, Portugal

[2] Univ Fed Itajuba, Campus Itabira, Itabira, Brazil

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS-ICCSA 2024 WORKSHOPS, PT II | 2024年 / 14816卷

关键词：

Forest Fires; Scheduling Problem; Optimization; Discrete-Event Simulation;

D O I：

10.1007/978-3-031-65223-3_26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In recent years, the number of forest fires has increased significantly. The main factors behind these disasters are rising temperatures and population growth. Optimization and simulation have been widely applied to forest firefighting problems, making it possible to improve the effectiveness and speed of firefighting actions. This work presents a forest firefighting resource scheduling problem, where a single firefighting resource is fighting 10 ignitions. A Genetic Algorithm (GA) is used to find the near-optimal sequence of actions, taking into account the maximization of the total unburned area. The solution found by the GA is evaluated using a Discrete-Event Simulation model developed in FlexSim software, thus validating the solution. Then, a simulation-based optimization approach is developed, involving uncertainty in some parameters.

引用

页码：383 / 396

页数：14

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