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Multi-objective design optimisation of repairable k-out-of-n subsystems in series with redundant dependency

机译:具有冗余依赖性的串联可修复k-of-n子系统的多目标设计优化

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摘要

Several researches have been investigated on Multi-Objective Redundancy Allocation Problems (MORAPs), but none of them have considered the redundant dependency at the design stage. This latter which is a special kind of failure dependency can affect significantly the system performance. Due to this fact, this paper deals with the multi-objective system design optimisation with dependent components by focusing on two objectives: maximisation of system availability and minimisation of system cost with components choice and weight constraints. A system consisting of many k-out-of-n repairable subsystems connected in series is considered. The components of a subsystem are supposed to be identical and may be dependent. They are selected from a set of available component types. In addition to the redundancy level and the number of repair teams allocated to each subsystem, the choice of components type and the dependency level are also considered as decision variables. Since the described problem is NP hard, we propose three multi-objective meta-heuristic algorithms based on Non-dominated Sorting Genetic Algorithm (NSGAII) and Strength Pareto Evolutionary Algorithm (SPEA II) with different constraints handling. An exact method is also applied. To analyse their performances, numerical applications are provided and comparisons based on different well-known metrics are presented.
机译:已经对多目标冗余分配问题(MORAP)进行了一些研究,但没有一个在设计阶段就考虑了冗余依赖性。后者是一种特殊的故障依赖性,会严重影响系统性能。由于这个事实,本文通过关注两个目标来处理具有相关组件的多目标系统设计优化:系统可用性的最大化和具有组件选择和权重约束的系统成本的最小化。考虑了一个由n个k-of-n可修复子系统串联组成的系统。子系统的组件应该是相同的,并且可能是相互依赖的。它们是从一组可用的组件类型中选择的。除了冗余级别和分配给每个子系统的维修团队数量之外,组件类型和依赖性级别的选择也被视为决策变量。由于所描述的问题是NP问题,因此我们提出了三种基于非支配排序遗传算法(NSGAII)和强度帕累托进化算法(SPEA II)的多目标元启发式算法,并采用了不同的约束处理方法。确切的方法也适用。为了分析它们的性能,提供了数值应用程序,并提出了基于不同知名指标的比较。

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