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Multi-objective availability-redundancy allocation problem for a system with repairable and non-repairable components

机译:具有可修复和不可修复组件的系统的多目标可用性-冗余分配问题

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摘要

Reliability is one of the most important characteristics of the electrical and mechanical systems with applications in the space communication industries, internet networks, telecommunication systems, power generation systems, and productive facilities. What adds to the importance of reliability in these systems are system complications, nature of competitive markets, and increasing production costs due to failures. This paper investigates availability optimization of a system using both repairable and non-repairable components, simultaneously. The availability-redundancy allocation problems involve the determination of component availability (i.e., life time and repair time of the components) and the redundancy levels that produce maximum system availability. These problems are often subject to some constraints on their components such as cost, weight, and volume. To maximize the availability and to minimize the total cost of the system, a new Mixed Integer Nonlinear Programming (MINLP) model is presented. To solve the proposed model, an improved version of the genetic algorithm is designed as an efficient meta-heuristic algorithm. Finally, in order to verify the efficiency of the proposed algorithm, a numerical example of a system is presented that consists of both repairable and non-repairable components.
机译:可靠性是机电系统的最重要特征之一,在空间通信行业,互联网网络,电信系统,发电系统和生产设施中都有应用。在这些系统中增加可靠性的重要性在于系统的复杂性,竞争市场的性质以及由于故障而增加的生产成本。本文研究了同时使用可修复和不可修复组件的系统可用性优化。可用性-冗余分配问题涉及确定组件可用性(即,组件的寿命和维修时间)以及产生最大系统可用性的冗余级别。这些问题通常在其组成部分上受到某些约束,例如成本,重量和体积。为了最大化可用性并最小化系统的总成本,提出了一种新的混合整数非线性规划(MINLP)模型。为了解决所提出的模型,将遗传算法的改进版本设计为有效的元启发式算法。最后,为了验证所提出算法的效率,给出了一个由可修复和不可修复组件组成的系统的数值示例。

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