Improved genetic algorithm for dynamic multi-UAVs target assignment at the end of logistics
Fang Hou, Zhuang Yufeng, Jingwen Han, Xiying Chen, Zhuang Yufeng · 2022
In unmanned logistics end distribution, task distribution is a problem that must be solved. In this paper, we calculate the distribution range that can be covered by multiple UAVs, and make distributed interconnection communication and calculation between multiple intelligent bodies, i.e., between multiple UAVs and ground platforms. In the process of executing the task, the distribution result is adjusted by real-time replanning, so that the total distance in the distribution result is minimized. After the UAV takes off and starts to execute the distribution task, the objective function model is established based on the real-time location of the UAV, the location of the end point of the movement, the length of the path of the task execution, and the time collaboration of the multi-UAV execution task as constraints, and solved using the Improved Genetic Algorithm. Through the results of simulation experiments, we can see that the task allocation strategy used in this paper can perform resource calculation more efficiently and get optimized allocation results.