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An improved particle swarm optimization algorithm for reliability- redundancy allocation problem with mixed redundancy strategy and heterogeneous components

机译：具有混合冗余策略和异构组件的可靠性-冗余分配问题的改进粒子群算法

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摘要

The reliability-redundancy allocation problem (RRAP) has been intensively studied to identify the optimal system design under several constraints, so as to maximize the system reliability as much as possible. Recently, the mixed redundancy strategy where both active redundant components and cold standby components can be simultaneously used by a subsystem has been introduced into the RRAP, leading to a more superior result than that of a subsystem with either active redundancy strategy or cold standby strategy. Nevertheless, in the existing studies, all the components deployed in a subsystem have to be homogeneous even if the mixed redundancy strategy is chosen. The strong premise is released in this paper by introducing heterogeneous components into the RRAP. The resulting optimization problem is resolved by proposing an improved particle swarm optimization (PSO) algorithm with stochastic perturbation nature. The efficiency of the proposed algorithm has been demonstrated by conducting a set of comparative studies on three benchmark problems. As observed in our study, the design flexibility introduced by our method can always yield a greater system reliability than that of the state-of-the-art methods. Most importantly, we also reveal that the switching reliability has significant influence on the optimal system configuration.
机译：对可靠性-冗余分配问题（RRAP）进行了深入研究，以确定在多个约束条件下的最优系统设计，从而尽可能地提高系统的可靠性。最近，RRAP中引入了混合冗余策略，在该策略中，子系统可以同时使用活动冗余组件和冷备用组件，从而获得比具有活动冗余策略或冷备用策略的子系统更好的结果。但是，在现有研究中，即使选择了混合冗余策略，子系统中部署的所有组件也必须是同质的。通过将异类组件引入RRAP，释放了强大的前提。通过提出一种具有随机摄动性质的改进的粒子群优化（PSO）算法，解决了由此产生的优化问题。通过对三个基准问题进行一组比较研究，证明了所提出算法的效率。正如我们的研究中所观察到的那样，我们的方法所带来的设计灵活性总会比最先进的方法产生更高的系统可靠性。最重要的是，我们还揭示了切换可靠性对最佳系统配置有重要影响。

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