This paper presents a fuzzy adaptive differential evolution (DE) for 3D UAV path planning. The path-planning problem is formulated as a multi-objective unconstrained optimization problem, with the aim of minimizing the fuel and the threat cost as well as finding the shortest path. DE is used for optimization where a fuzzy logic controller is used to find the parameter values of DE during the optimization process. The mutation operation is modified in such a way to strike a balance between the DE/rand/1 and DE/best/1 versions. This method is compared with both DE/rand/1 and DE/best/1 and it was found to perform relatively better than both the classical variations. Often finding the right parameter values for DE can be tedious, this method will give freedom from the process of finding the parameter values for acceptable performance of 3D path planning optimization.
