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...
Saved in:
Published in | IEEJ transactions on electrical and electronic engineering Vol. 11; no. 6; pp. 753 - 759 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Hoboken
Wiley Subscription Services, Inc., A Wiley Company
01.11.2016
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
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 content type line 14 content type line 23 |
ISSN: | 1931-4973 1931-4981 |
DOI: | 10.1002/tee.22300 |