To find the best mode for system design in reliability optimization, risk engineers around the world use the importance measure as a basic tool. This paper introduces a new importance measure taking into account minimal path sets of the system. It helps to optimize the system designs that occur in many situations. For instance, this importance measure can be used (a) in identifying important components of any complex system and (b) solving constrained redundancy optimization problems. This is illustrated by providing two heuristic algorithms. In the first algorithm, this measure is used to find important components of any complex system ensuring improved system reliability. The second algorithm is used to solve a constrained redundancy optimization problem for any general coherent system giving (near) optimal solutions in 1-neighborhood. The results show that the new importance measure is easily applicable, unlike the classical ones. Hence, it serves as a very useful tool in measuring the important component(s) and solving constrained redundancy optimization problems of complex systems. Thus, it can be considered as a good alternative to the existing importance measures.

为了在可靠性优化中找到最佳的系统设计模式，全世界的风险工程师都将重要性评估作为基本工具。本文介绍了一种新的重要性度量，其中考虑了系统的最小路径集。它有助于优化在许多情况下发生的系统设计。例如，此重要性度量可用于（a）识别任何复杂系统的重要组件，以及（b）解决约束冗余优化问题。这通过提供两种启发式算法来说明。在第一种算法中，此措施用于查找任何复杂系统的重要组件，从而确保提高的系统可靠性。第二种算法用于解决在1个邻域中给出（接近）最优解的任何通用相干系统的约束冗余优化问题。结果表明，与传统方法不同，新的重要性方法易于应用。因此，它在测量重要组件和解决复杂系统的受限冗余优化问题时，是非常有用的工具。因此，可以认为它是现有重要措施的良好替代方案。