Cooperative task allocation for multi heterogeneous aerial vehicles using particle swarm optimization algorithm and entropy weight method

Reasonable and effective task allocation strategy is the premise to ensure the successful completion of combat missions, which is of great significance to improve the overall operational effectiveness of the cluster. In this paper, a cooperative task allocation method for multi heterogeneous aerial vehicles under strong space-time constraints using particle swarm optimization (PSO) algorithm and entropy weight method is presented. Specifically, the problem of cooperative task allocation is formulated as a multi-objective optimization problem under multi-constraint conditions, and the requirement of required time of arrival (RTA) of time-sensitive targets is considered. Then, the PSO algorithm is applied to solve the task allocation model. Especially, task sequence is introduced into the coding of the feasible solutions, and task urgency is employed to update the particle position. Furthermore, the entropy weight method is introduced into task assignment scheme decision-making. Finally, a simulation is given to illustrate the validity.