System reliability optimization is a key element for a competitive and safe industrial plant. This paper addresses the multiobjective system reliability optimization in the presence of fuzzy data. A framework solution approach is proposed and based on four steps: defuzzify the data into crisp values by the ranking function procedure, the defuzzified problems are solved by the non‐sorting genetic algorithms II and III (NSGA‐II and NSGA‐III), the Pareto fronts are compared by the spacing method for selecting the best one, and then the best Pareto front is reduced by the clustering analysis for helping the decision maker. A case study presented in the literature as a mono‐objective redundancy allocation problem with fuzzy data is investigated in the present paper as multiobjective redundancy allocation and reliability‐redundancy allocation problems show the applicability of the approach.

中文翻译：

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遗传算法与聚类分析相结合的模糊多目标系统可靠性优化

系统可靠性优化是竞争和安全的工业工厂的关键要素。本文针对存在模糊数据的情况下的多目标系统可靠性优化问题进行了探讨。提出了一种框架解决方案方法，该方法基于四个步骤：通过排序函数程序将数据解模糊为清晰的值，通过非分类遗传算法II和III（NSGA-II和NSGA-III）解决解模糊的问题，通过间隔法比较帕累托锋，以选择最佳的帕累托锋，然后通过聚类分析减少最佳帕累托锋，以帮助决策者。