Title
Multi-UAV Objective Assignment Using Hungarian Fusion Genetic Algorithm
Abstract
In the background of air combat, the situation between multiple unmanned aerial vehicle (multi-UAV) and objectives has a certain impact on the task assignment. In order to improve the efficiency of assignment and obtain the best assignment scheme during the process of performing tasks, this paper proposes a method to evaluate the situation at a certain time. This method is the basis for establishing a multi-UAV objective assignment model. For solving the model, this paper presents the Hungarian fusion Genetic Algorithm. It first uses the feasible solutions solved by the Hungarian algorithm as the elite individuals in the initial population of the genetic algorithm, and then uses the objective function in the assignment model as the fitness function to optimize the results. The algorithm solves the problem that the assignment result of the Hungarian algorithm is not unique, and optimizes the drawback that the traditional Genetic Algorithm is prone to fall into local optimum. The simulation verified the effectiveness of the situational assessment method and the improved algorithm.
Year
DOI
Venue
2022
10.1109/ACCESS.2022.3168359
IEEE ACCESS
Keywords
DocType
Volume
Missiles, Genetic algorithms, Autonomous aerial vehicles, Azimuth, Task analysis, Atmospheric modeling, Aircraft, Situational assessment method, objective assignment model, Hungarian algorithm, genetic algorithm
Journal
10
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Jiang Yan100.34
Dao Bo Wang2215.92
Bai Tingting300.34
Yan Zongyuan400.34