Research on Improved NSGA-II Algorithm and Its Application in Emergency Management
This paper constructs a dynamic multiobjective location model; three objectives are considered: the first objective maximizes the total utility of relief supplies, the second objective minimizes the number of temporary facilities needed to operate, and the third objective maximizes the satisfaction...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2018/1306341 |
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doaj-1357c67c62df4cd2a0221f1e4d5376a32020-11-25T00:06:32ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/13063411306341Research on Improved NSGA-II Algorithm and Its Application in Emergency ManagementXi Fang0Wenwen Wang1Lang He2Zhangcan Huang3Yang Liu4Liang Zhang5Hubei Collaborative Innovation Center for Early Warning and Emergency Response Technology, Wuhan, ChinaWuhan University of Technology, Wuhan, ChinaHubei Collaborative Innovation Center for Early Warning and Emergency Response Technology, Wuhan, ChinaWuhan University of Technology, Wuhan, ChinaWuhan University of Technology, Wuhan, ChinaWuhan University of Technology, Wuhan, ChinaThis paper constructs a dynamic multiobjective location model; three objectives are considered: the first objective maximizes the total utility of relief supplies, the second objective minimizes the number of temporary facilities needed to operate, and the third objective maximizes the satisfaction for all demand points. We propose an improved NSGA-II to solve the optimization problem. The computational experiments are divided into two sections: In the first procedure, the numerical experiment is constructed by the classical functions ZDT1, ZDT2, and DTLZ2; the results show that the proposed algorithm generates the exact Pareto front, and the convergence and uniformity of the proposed algorithm are better than the NSGA-II and MOEA/D. In the second procedure, the simulation experiment is constructed by a case in emergency management; the results show that the proposed algorithm is more reasonable than the traditional algorithms NSGA-II and MOEA/D in terms of the three objectives. It is proved that the improved NSGA-II algorithm, which is proposed in this paper, has high precision application for the sudden disaster crisis and emergency management.http://dx.doi.org/10.1155/2018/1306341 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xi Fang Wenwen Wang Lang He Zhangcan Huang Yang Liu Liang Zhang |
spellingShingle |
Xi Fang Wenwen Wang Lang He Zhangcan Huang Yang Liu Liang Zhang Research on Improved NSGA-II Algorithm and Its Application in Emergency Management Mathematical Problems in Engineering |
author_facet |
Xi Fang Wenwen Wang Lang He Zhangcan Huang Yang Liu Liang Zhang |
author_sort |
Xi Fang |
title |
Research on Improved NSGA-II Algorithm and Its Application in Emergency Management |
title_short |
Research on Improved NSGA-II Algorithm and Its Application in Emergency Management |
title_full |
Research on Improved NSGA-II Algorithm and Its Application in Emergency Management |
title_fullStr |
Research on Improved NSGA-II Algorithm and Its Application in Emergency Management |
title_full_unstemmed |
Research on Improved NSGA-II Algorithm and Its Application in Emergency Management |
title_sort |
research on improved nsga-ii algorithm and its application in emergency management |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2018-01-01 |
description |
This paper constructs a dynamic multiobjective location model; three objectives are considered: the first objective maximizes the total utility of relief supplies, the second objective minimizes the number of temporary facilities needed to operate, and the third objective maximizes the satisfaction for all demand points. We propose an improved NSGA-II to solve the optimization problem. The computational experiments are divided into two sections: In the first procedure, the numerical experiment is constructed by the classical functions ZDT1, ZDT2, and DTLZ2; the results show that the proposed algorithm generates the exact Pareto front, and the convergence and uniformity of the proposed algorithm are better than the NSGA-II and MOEA/D. In the second procedure, the simulation experiment is constructed by a case in emergency management; the results show that the proposed algorithm is more reasonable than the traditional algorithms NSGA-II and MOEA/D in terms of the three objectives. It is proved that the improved NSGA-II algorithm, which is proposed in this paper, has high precision application for the sudden disaster crisis and emergency management. |
url |
http://dx.doi.org/10.1155/2018/1306341 |
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