Abstract

This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces).

Details

Title
Emergency logistics for wildfire suppression based on forecasted disaster evolution
Author
Yang, Zhongzhen 1 ; Guo, Liquan 1 ; Yang, Zaili 2   VIAFID ORCID Logo 

 Transportation Management College, Dalian Maritime University, Dalian, China 
 Transportation Management College, Dalian Maritime University, Dalian, China; Liverpool Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool, UK 
Pages
917-937
Publication year
2019
Publication date
Dec 2019
Publisher
Springer Nature B.V.
ISSN
02545330
e-ISSN
15729338
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2320899995
Copyright
Annals of Operations Research is a copyright of Springer, (2017). All Rights Reserved., © 2017. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.