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...

Full description

Bibliographic Details
Main Authors: Xi Fang, Wenwen Wang, Lang He, Zhangcan Huang, Yang Liu, Liang Zhang
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2018/1306341
id doaj-1357c67c62df4cd2a0221f1e4d5376a3
record_format Article
spelling 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
work_keys_str_mv AT xifang researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
AT wenwenwang researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
AT langhe researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
AT zhangcanhuang researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
AT yangliu researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
AT liangzhang researchonimprovednsgaiialgorithmanditsapplicationinemergencymanagement
_version_ 1725421605639684096