To solve the problem of UAV target strikes in complex urban environments， a UAV target strike method based on the electric eel foraging optimization （EEFO） algorithm is proposed. First， the method sets up two scenarios， namely the sparse environment without enemy defense and the dense environment with enemy defense， and designs corresponding constraint conditions and trajectory optimization cost functions to meet the flight needs in urban environments. Then， the EEFO algorithm is used to plan a reasonable target strike trajectory for the UAV. Finally， the flight trajectory and fitness value of the EEFO algorithm are obtained and compared with those of the other five algorithms： SO， SCA， WOA， MFO， and HHO. The experimental results show that in a sparse environment with enemy defense， the EEFO algorithm has higher trajectory planning efficiency and stability than the other five algorithms. It consumes the smallest trajectory cost and converges faster. In the dense environment with enemy defense， the EEFO algorithm has the optimal planned target strike trajectory and a better convergence trend of the consumed trajectory cost compared to the other five algorithms， with the highest task completion degree and better performance.
