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Multi-UAV Objective Assignment Using Hungarian Fusion Genetic Algorithm
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DOI：10.1109/ACCESS.2022.3168359.png)
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Abstract
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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.
Keywords:
Missiles
Genetic algorithms
Autonomous aerial vehicles
Azimuth
Task analysis
Atmospheric modeling
Aircraft
Situational assessment method
objective assignment model
Hungarian algorithm
genetic algorithm
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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