基于区间直觉模糊决策的多无人机任务分配方法

Multi-UAV Task Assignment Method Based on Interval-valued Intuition Fuzzy Decision Making

针对多无人机在不确定环境下面向SEAD约束的任务分配问题,提出一种基于区间直觉模糊决策的多无人机任务分配方法。构建面向不确定环境下无人机的任务分配数学模型,将无人机和任务的不确定信息用区间直觉模糊数表示;借助TOPSIS原理,考虑区间直觉模糊数的曼哈顿距离和犹豫度对区间直觉模糊数进行比较,采用改进后的离散差分进化算法求解得到最优的任务分配方案。结果表明:该分配模型合理,算法具有较好的收敛性。

Aiming at the problem of task assignment to multiple UAV on uncertain SEAD mission environment, a method based on interval-valued intuition fuzzy decision making is proposed. The mathematical model of task allocation is constructed, and the uncertain information of UAVs and tasks is represented by interval-valued intuition fuzzy numbers. By using the principle of TOPSIS, the Manhattan distance and hesitancy of the numbers is used to compare the interval-valued intuition fuzzy numbers. Additionally, an improved discrete differential evolution algorithm is used to solve the task allocation problem. The simulation results indicate that the allocation model has good feasibility and the algorithm has good convergence.