UAV optimal routing based on reference vector guided evolutionary algorithm

In UAV navigation, the simultaneous minimization of distance traveled and the threat of radar detection is two criteria in many military applications. The use of many-objective evolutionary algorithms in problems with conflicting goals can play an effective role in increasing the efficiency of these problems. In this research, the multi-purpose UAV route planning problem is considered and a many-objective optimization algorithm is presented in a multi-purpose UAV route planning problem. The proposed solution method is a reference vector evolutionary algorithm (RVEA). In this research, a platform in the MATLAB software, which is called PlatEMO, has been used. The proposed method is compared and evaluated with other many-objective and multi-objective evolutionary algorithms that have been presented recently and the results are obtained with a volume evaluation criterion that covers all the necessary categories (convergence, diversity, and cardinality). Give, express. The problem has been tested on two groups of optimization problems. Comparing the presented results, it is observed that the reference vector evolutionary algorithm has a better performance than other compared algorithms, and the convergence rate, diversity, and robustness of this algorithm is higher than other compared algorithms.