Multi-UAVs Target Attack Based on Improved Genetic Algorithm
Jiarui Su, Juntong Qi, Chong Wu, Mingming Wang, Jinjin Guo · 2020
Task assignment is the main conundrum of multiple unmanned aerial vehicles (multi-UAVs) cooperative task execution, which has great research value. To solve the problem of task scheduling for multi-UAVs, a method based on improved genetic algorithm is proposed in this paper. Firstly, a mathematical model of task assignment is established based on the application environment of multi-UAVs attacking targets. Secondly, aiming at the problem of slow convergence speed and easy to fall into local extremum of genetic algorithm, the improved Metropolis criterion of simulated annealing algorithm is introduced into the genetic algorithm. Finally, the simulation results show that the improved genetic algorithm can reduce the amount of calculation, improve the quality of the results, and solve the task assignment problem of multi-UAVs more effectively.