A Differential Evolution for Task Allocation for Multi-UAVs with No-Fly Zone
Na Wang, Qingzheng Xu, Feifan Liao, Weihu Zhao, Zhiyuan Zhao, Lei Wang · 2023
Unmanned aerial vehicles (UAVs) have significant prospects in military and civilian fields. Multi-UAVs can cooperatively complete tasks more efficiently and economically than a single UAV. As a typical coordination pattern for multi-UAVs, task allocation is a combinatorial optimization problem by which they are allocated to accomplish many tasks. To date, several algorithms have been proposed for varied scenario. In this paper, the task allocation problem for multi-UAVs with no-fly zone is studied. First, the no-fly zone is defined as a circular in 2D surface, and then two accurate and fast approaches are proposed respectively, in order to calculate the flight distance with no-fly zone. The original differential evolution (DE) cannot be directly applied to this optimization problem due to its discrete feasible solution. Therefore, some key operations of DE are modified to suit the needs of this optimization problem as follows: solution coding, mutation operation, crossover operation, etc. To verify the proposed algorithm, some experiments are done on 10 UAVs and 10 tasks. For both simple and complex cases, the experimental results confirm that the mathematical model constructed in this paper is reasonable, and the proposed DE is effective, especially for task allocation problem for multi-UAVs with no-fly zones.