A Hierarchical Multi-objective Programming Approach to Planning Locations for Macro and Micro Fire Stations

Gong, Xinghan; Liang, Jun; Zeng, Yiping; Meng, Fanman; Fong, Simon; Yang, Lili

doi:10.1007/978-3-031-17422-3_16

Cited by 1 publication

(1 citation statement)

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“…Some studies proposed fuzzy multi-objective programming combined with a genetic algorithm to optimize the location of the fire stations [21]. They appropriately converted the original fuzzy multiple objectives into a single unified goal based on the evaluation of experts [22]. Since cost is a factor that constrains the number of resources that can be dispatched, some studies have proposed a multi-resource scheduling method that combines the features of fire, labor, and cost to schedule firefighting resources.…”

Section: Introductionmentioning

confidence: 99%

An Event-Response Tree-Based Resource Scheduling Method for Wildfire Fighting

Zhou

Zhang

2023

Forests

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Dispatching firefighting resources effectively plays a vital role in wildfire management. To control the fire in a timely manner, resources should be dispatched in an effective and reasonable way. Moreover, the relationship between various resource-dispatching processes should be intuitive for firefighters to make decisions. In this paper, we propose a novel event-response tree-based model to dispatch different kinds of firefighting resources based on the fire suppression index (SI), which evaluates the effect of fire suppression by considering the time, cost, and effect of dispatching resources. To validate the proposed method, we compared it with the widely used mixed-integer programming (MIP) by using the historical fire data of Nanjing Laoshan National Forest Park. The results showed that the E-R tree-based resource scheduling can effectively schedule resources as well as the MIP model. Moreover, the relationship between various resource-dispatching processes in the proposed model is clear and intuitive for firefighters to make decisions.

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Section: Introductionmentioning

confidence: 99%