<![CDATA[The systematic examination of piping is essential for the successful implementation of risk-based inspection. The ineffective execution of this activity increases the risk of equipment failure and unnecessary costs. Therefore, this study aims to address the challenge of optimizing inspection planning for oil and gas piping systems within budgetary and operational constraints. The most effective inspection methods are selected to determine the optimal inspection interval. A multi-objective optimization model based on the non-dominated sorting genetic algorithm-II is applied to simultaneously minimize the probability of failure and optimize total inspection costs. The adopted methodology, which differs from traditional methods, eliminates reliance on predefined risk thresholds and explicit failure-consequence evaluations by directly incorporating inspection costs. Additionally, the best-performing model achieves an efficient solution by reducing the total probability of failure from 1.631 10-1 to 0.8975 10-1. The application model further provides a robust decision-support tool for efficient inspection planning, increases inspection effectiveness, and reduces the risk of failure. These developments form the basis for effective decision-making to support the implementation of asset integrity management through efficient inspection planning.]]>
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