All human-engineered systems and devices have a finite lifespan and are subject to potential failure at any time, which can lead to equipment breakdown or total system collapse. The primary objective of this study is the multi-objective optimization of preventive maintenance scheduling for networked systems. To ensure reliable network system operation, achieve functional stability, or restore a failed system to its normal operational state under various conditions, specific strategies and policies are proposed and analyzed. Ultimately, a networked system is modeled using a metaheuristic algorithm approach, and its parameters are optimized. The impact of preventive maintenance on enhancing system reliability and reducing operational costs is investigated using the NSGA-II algorithm, implemented in MATLAB software. By examining stochastic variables at different time points and assessing their cost implications, a Pareto front is generated. This front provides a spectrum of solutions, facilitating the selection of a high-reliability configuration at the minimal feasible cost. Analysis of the obtained Pareto front indicates that, considering the minimum acceptable average, the optimal trade-off between the highest system reliability and the most reasonable cost lies within the mid-range of the frontier. This optimal region offers operational flexibility, allowing decision-makers to select an appropriate solution point based on the specific requirements and constraints of the system in different working conditions.
Shirani et al. (2025) studied this question.