Emergency scheduling for forest fires subject to limited rescue team resources and priority disaster areas

To enable immediate and efficient emergency scheduling during forest fires, we propose a novel emergency scheduling model for such fires subject to priority disaster areas and limited rescue team resources to minimize the total travel distance for rescue teams. Moreover, a hybrid intelligent algorit...

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Published inIEEJ transactions on electrical and electronic engineering Vol. 11; no. 6; pp. 753 - 759
Main Authors Ren, Yaping, Tian, Guangdong
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.11.2016
Wiley Subscription Services, Inc
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Summary:To enable immediate and efficient emergency scheduling during forest fires, we propose a novel emergency scheduling model for such fires subject to priority disaster areas and limited rescue team resources to minimize the total travel distance for rescue teams. Moreover, a hybrid intelligent algorithm integrating genetic algorithm (GA) and particle swarm optimization (PSO) is adopted to solve the proposed model. A case study is presented to illustrate the proposed model and the effectiveness of the proposed algorithm. The goal of this work is to analyze the emergency scheduling problem of forest fires subject to limited rescue teams and priority disaster areas. Both theoretical and simulation results demonstrate that the proposed model can perform effectively the quantitative analysis of an emergency involving forest fires. Such results can help decision makers to make better judgment when dealing with an emergency involving fires. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Bibliography:Heilongjiang Province of China - No. LBH-TZ0501; No. LBH-Z13005
ArticleID:TEE22300
istex:C13D7756225F30CDD4BF20EAE74210AA6902AFC7
ark:/67375/WNG-02CH7MVF-2
National Natural Science Foundation of China - No. 51405075; No. 51561125002
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1931-4973
1931-4981
DOI:10.1002/tee.22300