A hybrid meta-heuristic DE/CS Algorithm for UCAV path planning
Gai‐Ge Wang, Lihong Guo, Hong Duan, Luo Liu, Heqi Wang, Jianbo Wang · 2012
Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which primarily centralizes on optimizing the flight route considering the different kinds of constrains. A new hybrid meta-heuristic differential evolution (DE) and cuckoo search (CS) algorithm is proposed to solve the UCAV path planning problem. DE is applied to optimize the process of selecting cuckoo of the CS model during the process of cuckoo in nest updating. Then, the UCAV can find the safe path by connecting the chosen nodes of the coordinates while avoiding the threat areas and costing minimum fuel. To prove the performance of DE/CS, it was compared with CS and other optimization methods. The results show that DE/CS is more effective and feasible in UCAV path planning than the other model.