Research on Improved NSGA-II Algorithm and Its Application in Emergency Management

Xi Fang,Yang Liu,Liang Zhang,Lang He,Zhangcan Huang,Wenwen Wang

doi:10.1155/2018/1306341

Abstract

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.

Highlights

In recent years, a significant growth in casualties and economic losses caused by frequent public emergencies such as earthquakes that happened in Wenchuan killing over 67000 people, flooding in Yangtze River, and the bombing that happened in Tianjin has been seen
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 multiobjective optimal evolutionary algorithms (MOEAs)/D
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

Summary

Introduction

A significant growth in casualties and economic losses caused by frequent public emergencies such as earthquakes that happened in Wenchuan killing over 67000 people, flooding in Yangtze River, and the bombing that happened in Tianjin has been seen. The emergency facility location is a multiobjective optimization problem which has to take quantities of complex factors into consideration, while the evolutionary algorithms such as GA [9], PSO [10], NSGA [11], and MOEA/D [12] are usually applied to solve such kind of problems. We propose the dynamic multiobjective location model, and we provide a novel solution algorithm for the stochastic model. This solution algorithm is based on a modification of elitism for NSGA-II algorithm, using a tabu search to improve the ability of local search. To solve the proposed model efficiently, an improved NSGA-II approach is proposed in Section 3; Section 4 discusses the proposed algorithm’s effectiveness based on the test functions ZDT1, ZDT2, and DTLZ2; Section 5 discusses the computational tests and implications arising from the study, and Section 6 summarizes the work with a discussion of the contribution of this paper, as well as the future direction

Multiobjective Optimization of Dynamic Location Model

An Improved NSGA-II

Simulations

Application Analyses

Conclusions