Multiple UAVs mission assignment based on modified Pigeon-inspired optimization algorithm

Unmanned aerial vehicles (UAVs) have shown their superiority for applications in performing military and civilian missions. In which, multiple UAVs mission assignment is becoming more important for today's military activities. So far, there have been many bio-inspired computation algorithms for solving multiple UAVs mission assignment problems, including particle swarm optimization (PSO), differential evolution algorithm (DE) and so on. However, deficiencies of these approaches exist inevitably, which cannot satisfy the requirements of dynamic mission assignment. In this paper, a new UAV assignment model focusing on the energy consumption of UAV is brought up which can be easily applied to intelligence algorithms. Meanwhile, we propose a new approach by applying the modified Pigeon-Inspired Optimization (PIO) algorithm to sovle the multiple UAVs mission assignment problem. The simulation results show that the modified PIO algorithm is more effective when compared with other state-of-the-art algorithms in addressing mission assignment problem for multiple UAVs.