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research
Emergency logistics for wildfire suppression based on forecasted disaster evolution
Authors
A Ager
A Buscarino
+74 more
A Charles
A Haghani
AJ Pedraza-Martinez
AK Rathi
AL Sullivan
AM Caunhye
AM Caunhye
B Balcik
C García
CG Rawls
D Alem
D Guha-Sapir
D Mandallaz
DB Matellini
DB Matellini
DI Iudin
DR Weise
EU Jacobson
F Fiedrich
F Liberatore
G Barbarosoğlu
G Chu
GB Yang
GH Tzeng
GJ Ji
GLW Perry
GY Wen
HJ Wang
IR Noble
J Martínez
JB Sheu
JB Sheu
JB Sheu
JB Sheu
JH Powell
JH Zhang
JM Zhu
JZ Yue
L Lei
L Özdamar
L Özdamar
Liquan Guo
M Rezaei-Malek
M Rodrigues
MA Krawchuk
MC Hoyos
MP Plucinski
MP Thompson
MS Chang
N Altay
N Altay
N Altay
PMJ Christie
R Oloruntoba
RH Chai
S Jin
S Wohlgemuth
SD Guikema
SR Yao
SS Wang
SX Miao
WJ Gutjahr
Xiangrong Zhang
Xiaoxia Huang
Y Lee
Y Page Le
Y Sun
Y Wei
Y Yuan
Zaili Yang
ZF Wang
ZH Hu
Zhongzhen Yang
ZW Wu
Publication date
Publisher
'Springer Science and Business Media LLC'
Doi
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). © 2017 The Author(s
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info:doi/10.1007%2Fs10479-017-...
Last time updated on 24/10/2020
LJMU Research Online (Liverpool John Moores University)
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Last time updated on 19/10/2017