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Maximization of system availability with failure dependency

机译:通过故障依赖性最大化系统可用性

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System availability optimization is one of the most challenging problems for modern complex systems. Basically, availability can be enhanced by increasing redundant components and the set of available maintenance teams which may lead to a dramatic increase in the overall system cost. In this context, this paper proposes an efficient optimization approach to get the best system design of series k - out - of - n : G system achieving the maximal possible steady system availability. A maximum system cost constraint should not be exceeded. The system cost is assumed composed of components purchase cost and repair cost. Moreover, since dependency is essential for reliability optimization problems, the redundant dependency which is a specific kind of failure dependency is taken into account. To solve the optimization problem, a resolution approach based on Genetic Algorithms (GA) is presented. Finally, a numerical application is carried out. The GA results are compared with the results given by LINGO which is a dedicated optimization software. It is used to validate the efficiency of the proposed approach.
机译:对于现代复杂系统,系统可用性优化是最具挑战性的问题之一。基本上,可以通过增加冗余组件和一组可用的维护团队来增强可用性,这可能导致总体系统成本急剧增加。在这种情况下,本文提出了一种有效的优化方法,以获取k-out-n-G系列的最佳系统设计,从而实现最大可能的稳定系统可用性。不应超过最大系统成本约束。假定系统成本由组件采购成本和维修成本组成。此外,由于依赖性对于可靠性优化问题是必不可少的,因此考虑了冗余依赖性,该冗余依赖性是一种特定的故障依赖性。为了解决优化问题,提出了一种基于遗传算法的遗传算法。最后,进行了数值应用。将GA结果与专用优化软件LINGO给出的结果进行比较。它用于验证所提出方法的效率。

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