Dynamic task allocation algorithm based on D-NSGA3

Task allocation is a key part of unmanned aerial vehicle (UAV) swarm. Although a large number of solving algorithms have been developed, there are few technologies that support task allocation algorithms in dynamic environments. Obviously, this is not in accord with the actual situation. The battlefield is changing rapidly, which may lead to the failure of the allocated tasks and the inability to allocate new tasks. In order to deal with this problem, this paper improves the original D-NSGA3 algorithm to adapt to the dynamic environment. The experimental results show that, compared with the original static algorithm, the proposed algorithm has better effect in solving the task allocation problem of high-dimensional multi-objective agent based on maximizing the number of successfully allocated tasks, maximizing the benefits of executing tasks, minimizing the consumption cost, and minimizing the time cost.