Multi-UAVs Cooperative Detection Based on Improved NSGA-II Algorithm

This paper proposes an improved (TS-NSGA-II) algorithm based on non-dominated sorted genetic algorithm-II (NSGA-II) algorithm, which is used for multiple unmanned aerial vehicles (multi-UAVs) to perform cooperative detection tasks in complex environments with multiple constraints. Firstly, under the consideration of various constraints, such as the maximum flight distance, the minimum safe distance and the minimum detection time of detection points, a multi-objective optimization function is established including detection profit, energy consumption and flight distance. Then, aiming at NSGA-II algorithm has the problem of falling into local extremum easily and getting the optimal solution slowly, the improved (TS-NSGA-II) algorithm is proposed, which adds the new population obtained by tabu search (TS) to the elite retention strategy of NSGA-II algorithm. Finally, the simulation results show that, compared with NSGA-II algorithm, the TS-NSGA-II algorithm can obtain better Pareto solution and has significant advantages in convergence, it can improve detection profit, reduce energy consumption and flight distance.