A new UAV assignment model based on PSO
Feng Pan, Xiaohui Hu, Russ Eberhart, Yaobin Chen · 2008
An unmanned aerial vehicle (UAV) assignment model requires allocating vehicles to targets to perform various tasks. It is a complex assignment problem with hard constraints, and potential dimensional explosion when the scenarios become more complicated and the size of problems increases. In this paper, a new UAV assignment model is proposed which reduces the dimension of the solution space and can be easily adapted by computational intelligence algorithms. In the proposed model a local version of particle swarm optimization (PSO) is applied to accomplish the optimization work. Numerical experimental results illustrate that it can efficiently achieve the optima and demonstrate the effectiveness of combining the model and a local version of PSO to solve complex UAV assignment problems.