针对多约束条件下的多无人机系统协同多任务分配问题(CMTAP),提出了利用多约束条件下的多车场车辆路径问题(MDVRPMC)对协同多任务分配问题进行建模,在设计基于Pareto最优的遗传模拟退火算法的基础上,对存在任务点动态时间窗口约束、任务类型约束、无人机任务能力约束等条件下的协同多任务分配问题进行了求解。实例仿真表明,该方法能有效地解决多无人机系统的协同多任务分配问题。 In order to solve the problem of cooperative multitask assignment (MTA) for multi-constraint UAV systems, a multi-vehicle routing problem with multiple constraints (MDVRPMC) is proposed to model the cooperative multi-tasking problem. Based on the design of Pareto Based on the optimal genetic simulated annealing algorithm, the problem of cooperative multi-tasking is solved under the conditions of dynamic time window constraints, task type constraints and UAV task capability constraints. The simulation results show that the proposed method can effectively solve the problem of coordinated multitasking in multi-UAV systems.