The generation system is an important part of the power system. The problem of generator maintenance scheduling is provided to construct optimal generators preventive maintenance schedules. It aims to improve economic benefits and achieve reliable operation of the power system while satisfying the system and maintenance constraints. In this paper, the binary crow search algorithm is proposed for solving the scheduling problem. This model would schedule maintenance scheme and commitment status of generating units while the objective functions are achieved. The crow search algorithm is a new meta-heuristic optimizer, which has its implementation very simple and easy compared to other optimization techniques. To verify the robustness and effectiveness of the proposed binary crow search optimizer, three test systems namely 6–unit, 21–unit system, and IEEE reliability test system are considered over the planning horizon of 52 weeks. The proposed optimizer is implemented in the MATLAB programming environment. Techno-economic aspects are considered for the generator's maintenance scheduling problem as reliability enhancement economic cost-minimizing issues. The proposed binary crow search optimizer is developed for single and multi-objective frameworks. The simulation results show the proposed binary crow search technique effectiveness and feasibility compared with previously optimizer in solving the generators maintenance scheduling problem with better convergence rate.