Attacking Strategy of Multiple Unmanned Surface Vehicles Based on DAMGWO Algorithm.

Unmanned combat system has received more and more attention with the development of modern weapons and equipment in recent years, which results in the application of unmanned surface vehicles (USVs) in the military. The USVs are designed to attack the protected hostile target with a minimum loss that use the lower attack capacity and a small number of attack USVs to reach the target. The USVs attack problem could be viewed as a multi-constrained task assignment problem. In this study, a novel algorithm is proposed, which is called DAMGWO, a grey wolf optimization (GWO) algorithm based on distributed auction mechanism (DAM). This algorithm combines DAM and GWO algorithm to constrain the wolf initialization, increasing the ability to break away from the local optimum. Furthermore a corresponding fitness function to evaluate the quality of this algorithm is proposed. The experimental results show that the proposed algorithm not only fully meets the requirements of the attacking strategy of multiple USVs that to attack the protected hostile target with a minimum loss, but also has better convergence than the traditional GWO algorithm and PSO algorithm.