A modified firefly algorithm for UCAV path planning

Path planning for uninhabited combat air vehicle (UCAV) is a complicated high dimension optimization problem, which mainly centralizes on optimizing the flight route considering the different kinds of constrains under complicated battle field environments. Original firefly algorithm (FA) is used to solve the UCAV path planning problem. Furthermore, a new modified firefly algorithm (MFA) is proposed to solve the UCAV path planning problem, and a modification is applied to exchange information between top fireflies during the process of the light intensity 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. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic FA. The realization procedure for original FA and this improved meta-heuristic approach MFA is also presented. To prove the performance of this proposed meta-heuristic method, MFA was compared with FA and other population-based optimization methods, such as, ACO, BBO, DE, ES, GA, PBIL, PSO and SGA. The experiment shows that the proposed approach is more effective and feasible in UCAV path planning than the other model.

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