Path planning for heterogeneous UAV swarm is always one of the significant topics of the mission planning system in various applications. Unfortunately, it remains a complex issue to obtain favorable solutions especially for heterogeneous UAVs and large-scale scattered regions. To solve this challenging problem, this work studies the coverage path planning problem to seek flight paths to visit all scatter regions and reduce the finish time of UAVs. A novel adaptive water wave optimization (WWO)-based planning approach (AWWO) is proposed by systematic adapting WWO metaheuristic. In the proposed approach, K-nearest neighbor algorithm is used to generate the initial wave swarm. Meanwhile, the propagation operator and wavelength calculation strategy are redesigned according to the knowledge of the problem to be solved to find the best flight path for each UAV. Experiments with randomly generated regions verify that the proposed approach AWWO performs better than several other approaches as far as the time cost of UAVs is concerned.