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

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.

An application of the NSGA-II algorithm in Pareto joint inversion of 2D magnetic and gravity data

“…NSGA-II found its application both in geophysical investigations (Schwarzbach et al 2005, Currenti et al 2014, Ayani et al 2020 and in other fields (Jeyadevi et al 2011, Wang et al 2017, Martínez et al 2020. It is still developing (Fang et al 2018) and has even been used as the basis to create some new algorithms (Liu et al 2020).…”

Multiobjective Optimized Dispatching for Integrated Energy System Based on Hierarchical Progressive Parallel NSGA-II Algorithm

“…Among the multiobjective genetic algorithms, the widely used algorithms are nondominated sorting genetic algorithm (NSGA) and nondominated sorting genetic algorithm-II (NSGA-II) [14][15][16].…”