基于DE-DPSO-GT-SA算法的协同多任务分配

针对无人机（UAV）编队的协同多任务分配问题（CMTAP），考虑双机协同探测、双机协同攻击的情况，结合时间约束、时序约束、时间间隔约束、载机弹药约束、任务能力约束等约束条件，扩展了协同多任务分配模型；将差分进化（DE）算法、郭涛（GT）算法、离散粒子群优化（DPSO）算法、模拟退火（SA）算法进行融合，提出了DE-DPSO-GT-SA算法，用以求解协同多任务分配问题。通过与多种算法进行比较，仿真试验结果表明，所提算法具有较好的收敛性能。 

Cooperative multi-task assignment based on DE-DPSO-GT-SA algorithm

Aimed at Cooperative Multi-Task Assignment Problem (CMTAP) of Unmanned Aerial Vehicle (UAV) formation, considering the situation of cooperative detection and attack of two aircraft, combining the constraint conditions of time constraint, time sequence constraint, time interval constraint, ammunition constraint and task capability constraint, the model of cooperative multi-task assignment is extended, and a mixed Differential Evolution (DE) and Guo Tao (GT) algorithm, Discrete Particle Swarm Optimization (DPSO) algorithm and Simulated Annealing(SA) algorithm are fused to propose a DE-DPSO-GT-SA algorithm to solve the cooperative multi-task assignment problem. The performance of DE-DPSO-GT-SA algorithm and that of other algorithms are compared. Simulation results show that DE-DPSO-GT-SA algorithm has better convergence performance than other algorithms.