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Multi-objective optimization in redundant system considering load sharing

机译：考虑负载分担的冗余系统多目标优化

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Reliability allocation problem (RAP) deals with the dilemma between reliability (or availability) increase and some undesirable consequences, as an increase in cost. Therefore, new installations or maintenance investments should be optimally allocated to maximize the reliability (or availability), considering all restrictions. This paper proposes a solution for the RAP problem, taking into account failure dependency among redundant components. Because of that, a stochastic approach, based on Markov Chain, is applied. The multi-objective problem is solved with NSGA-II (Non-Dominated Sorting Genetic Algorithm II), assuming availability and overall costs as objective functions. Two examples are tested with the proposed approach. The first case is a hypothetical system with 5 subsystems in series. The second example is a real industrial application. In both cases, a Pareto front is obtained, allowing an analysis of viable solutions to be adopted. Additionally, the failure dependency effect is also present in the optimization results. Therefore, it is possible to investigate the influence on the system availability and final cost.
机译：可靠性分配问题（RAP）解决了可靠性（或可用性）增加和一些不希望的后果之间的难题，即成本增加。因此，在考虑所有限制的情况下，应最佳地分配新的安装或维护投资，以最大程度地提高可靠性（或可用性）。考虑到冗余组件之间的故障相关性，本文提出了一种针对RAP问题的解决方案。因此，应用了基于马尔可夫链的随机方法。假设可用性和总成本为目标函数，则使用NSGA-II（非主导排序遗传算法II）解决多目标问题。使用所提出的方法测试了两个示例。第一种情况是一个假设的系统，该系统具有5个串联的子系统。第二个例子是一个实际的工业应用。在这两种情况下，都获得了帕累托前沿，从而可以对可行的解决方案进行分析。此外，优化结果中还存在故障依赖效应。因此，可以调查对系统可用性和最终成本的影响。

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