Toward Efficient Management of Large Fires: A Mixed Integer Programming Model and Two Iterative Approaches
Toward Efficient Management of Large Fires: A Mixed Integer Programming Model and Two Iterative Approaches
复制标题
实现大型火灾的高效管理：混合整数规划模型和两种迭代方法
DOI：
10.1093/forestscience/57.5.435
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
T. Hall
中科院分区：
文献类型：
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作者：
Yu Wei;D. Rideout;T. Hall
在这项研究中，我们开发了一个优化模型和两个迭代方法来提高大型火灾管理的效率。该模型跨时间和空间分配灭火努力，以在规定的持续时间内将火灾损失降至最低。它与以前的研究不同，它用基于进度的火灾损失控制取代了简化的火灾控制规则。这是通过扩展最小旅行时间算法来建立大型火灾扑救模型来实现的。混合整数规划用于集成火灾行为、消防员安全和风险值等空间信息，以指导大型火灾扑救。对特定时间抑制分配的关注通过使用不同逻辑过程的两种迭代方法来建模。测试案例演示了该模型如何组合空间数据以支持针对一场火灾或多场同时发生的火灾的扑救决策。红杉国家公园和国王峡谷国家公园的30场随机模拟火灾也被安排扑灭。结果表明，灭火延时会显著增加火灾损失。仿真结果表明，迭代方法A能更有效地将抑制工作分配到较短的时间段。
In this study, we developed an optimization model and two iterative approaches to improve the efficiency of large fire management. This model allocates suppression effort across time and space to minimize fire loss within a defined duration. It departs from previous research by replacing simplified fire containment rules with progress-based fire loss control. This is accomplished by extending the minimum travel time algorithm to build a large fire suppression model. Mixed integer programming is used to integrate spatial information such as fire behavior, firefighter safety, and values at risk to guide large fire suppression. The concern of time-specific suppression allocation is modeled through two iterative approaches using different logical procedures. Test cases demonstrate how this model assembles spatial data to support suppression decisions for one fire or multiple simultaneous fires. Suppression is also scheduled across 30 randomly simulated fires in Sequoia and Kings Canyon National Parks. Results demonstrate that suppression delay can significantly increase fire loss. Simulation results show that iterative approach A is more efficient in distributing suppression effort into short time periods.