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Design optimization and redundant dependency study of series k — out — of — n : G repairable systems

机译：n：G 可修复系统中的 k —系列的设计优化和冗余依赖性研究

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Abstract: This paper proposes a new optimization approach to find the best redundancy allocation of dependent repairable series k—out—of—n : G system using ant colony optimization. A model for the failure redundant dependency between the system components is formulated. It is considered in the system performance evaluation. An optimization model is then derived to be solved using the software LINGO and the proposed ACO algorithm. The objective consists of minimizing the system cost while satisfying a required level of system availability. The best system configuration in terms of number of components and number of repair teams in each subsystem is to be determined. The components are characterized by their failure rate, repair rate, unit acquisition cost and unit repair cost. In order to validate the proposed approach, an illustrative example is applied. A comparison between LINGO and ACO results is facilitated. The results show that the redundant dependency may positively affect the design configuration and the system cost. Furthermore, the proposed ACO outperforms LINGO for large scale systems in term of solution quality.
机译：摘要：本文提出了一种新的优化方法，即使用蚁群算法来找到依赖可修复序列k-out-ofn：G系统的最佳冗余分配。建立了系统组件之间故障冗余依赖关系的模型。在系统性能评估中考虑它。然后使用LINGO软件和所提出的ACO算法导出要求解的优化模型。目的是在满足所需级别的系统可用性的同时，将系统成本降至最低。确定每个子系统中组件数量和维修团队数量方面的最佳系统配置。这些组件的特征在于其故障率，维修率，单位购置成本和单位维修成本。为了验证所提出的方法，应用了说明性示例。简化了LINGO和ACO结果之间的比较。结果表明，冗余依赖性可能会对设计配置和系统成本产生积极影响。此外，就解决方案质量而言，拟议的ACO在大型系统方面优于LINGO。

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