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 in the aim of minimizing the fuel and the threat cost as well as finding the shortest path. A fuzzy logic controller is used to find the parameter values of DE during this optimization process. The mutation operation of DE is modified in a way to strike a balance between the DE/rand/1 and DE/best/1 strategies. This method is compared with both DE/rand/1 and DE/best/1 and it relatively outperformed both the classical variations. As it is often tedious to find the right parameter values for DE, this method will give freedom from the process of finding the parameter values for the acceptable performance in 3D path planning optimization.