Selective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there are situations the system needs small intervals or break for maintenance actions, during the intervals expert carried out the maintenance actions to replace or repair the deteriorated components of the systems. Because of the uncertainty associated with the component’s operational time, failure, and next mission duration create a new challenge in determining optimal components allocation and evaluating future missions successfully. In this paper, a multi-objective selective maintenance allocation problem is formulated with fuzzy parameters under neutrosophic environment. A new defuzzification technique is introduced based on beta distribution to convert fuzzy parameters into crisp values. The neutrosophic goal programming technique is used to determine the compromise allocation of replaceable and repairable components based on the system reliability optimization. A numerical illustration is used to validate the model and ascertain its effectiveness. The result is compared with two other approaches and found to be better. The method is flexible and straightforward and can be solved using any available commercial packages. The extension of the concept can be useful to other complex system reliability optimization.

选择性维护问题在可靠性优化决策问题中起着至关重要的作用。系统是由几个组件组成的配置，在某些情况下，系统需要较小的间隔或需要中断才能执行维护操作，在此间隔期间，专家会执行维护操作以更换或维修系统的退化组件。由于与组件的运行时间，故障和下一次任务持续时间相关的不确定性，在确定最佳组件分配和成功评估未来任务方面提出了新的挑战。本文在中智环境下用模糊参数提出了多目标选择性维修分配问题。引入了一种新的基于β分布的去模糊技术，可以将模糊参数转换为清晰的值。中智目标编程技术用于基于系统可靠性优化来确定可替换和可修复组件的折衷分配。使用数字图示来验证模型并确定其有效性。将结果与其他两种方法进行比较，发现效果更好。该方法灵活，直接，可以使用任何可用的商业软件包解决。该概念的扩展对于其他复杂的系统可靠性优化很有用。使用数字图示来验证模型并确定其有效性。将结果与其他两种方法进行比较，发现效果更好。该方法灵活，直接，可以使用任何可用的商业软件包解决。该概念的扩展对于其他复杂的系统可靠性优化很有用。使用数字图示来验证模型并确定其有效性。将结果与其他两种方法进行比较，发现效果更好。该方法灵活，直接，可以使用任何可用的商业软件包解决。该概念的扩展对于其他复杂的系统可靠性优化很有用。