The preventive inspection and maintenance interval (PIMI) optimization model for series systems, subsystems, and components of continuously functioning coal-fired power plants is presented in this work. Maximizing system availability while lowering maintenance costs are the goal functions. The metaheuristic optimization algorithms such as multi-objective particle swarm optimization (MOPSO) and Genetic Algorithm (GA) are used to determine the global optimum among the nonlinear objective functions under specific restrictions. It is found that metaheuristic optimization algorithms may effectively identify the global optimum of multi-objective nonlinear PIMI optimization functions under certain circumstances. The results show that the suggested PIMI optimization model may significantly decrease the failure frequency along with the annual maintenance cost in one hand and increase the plant’s availability on the other. After all, the suggested PIMI model may increase the plant’s annual profit.