This study deals with the task assignment problem of heterogeneous unmanned aerial vehicle (UAV) system with the limited resources and task priority constraints. The optimization model which comprehensively considers the resource consumption, task completion effect, and workload balance is formulated. Then, a concept of fuzzy elite degree is proposed to optimize and balance the transmission of good genes and the variation strength of population during the operations of algorithm. Based on the concept, we propose the fuzzy elite strategy genetic algorithm (FESGA) to efficiently solve the complex task assignment problem. In the proposed algorithm, two unlock methods are presented to solve the deadlock problem in the random optimization process; a sudden threat countermeasure (STC) mechanism is presented to help the algorithm quickly respond to the change of task environment caused by sudden threats. The simulation results demonstrate the superiority of the proposed algorithm. Meanwhile, the effectiveness and feasibility of the algorithm in workload balance and task priority constraints are verified.

该研究解决了资源有限和任务优先级受限的异构无人机系统的任务分配问题。建立了综合考虑资源消耗，任务完成效果和工作量平衡的优化模型。然后，提出了模糊精英度的概念，以优化和平衡算法运行过程中良好基因的传递和种群的变异强度。基于此概念，我们提出了模糊精英策略遗传算法（FESGA），以有效解决复杂的任务分配问题。该算法提出了两种解锁方法来解决随机优化过程中的死锁问题。提出了一种突发威胁对策（STC）机制，可以帮助算法快速响应突发威胁导致的任务环境变化。仿真结果证明了该算法的优越性。同时，验证了该算法在工作量均衡和任务优先级约束方面的有效性和可行性。