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Optimal Design Of Binary Weighted K-out-of-n Systems

机译:二元加权K-out-n系统的优化设计

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In this paper, we consider the optimal design of the binary weighted fc-out-of-n system. The binary weighted k-out-of-n: G system works if and only if the total utility of all working components is at least k. In the design process, we need to evaluate system reliability repetitively. The universal generating function (UGF) approach is used for this purpose when the system size is small or moderate. When the size of the system is large, the recursive approach is used, which is more efficient. Two optimal models are formulated. One is to minimize the expected total cost while guaranteeing the system reliability higher than a pre-specified value; the other is to maximize the system reliability with the constraints on total system cost. Genetic algorithms (GA) and Tabu Search (TS) methods are both used to solve the proposed optimization models. Since the key to a good TS algorithm is usually quite problem-specific policies and memory structures, there is no existing general TS tool available. Therefore more details of the TS approach used in this paper are discussed than the GA approach. The results obtained with these two methods are compared. The results illustrate that both methods are powerful tools for solving these kinds of problems. However TS is more efficient than GA in computation. The materials in this paper have been published in 19.
机译:在本文中,我们考虑了二进制加权fc-out-of-n系统的优化设计。当且仅当所有工作组件的总效用至少为k时,二进制加权k-of-n:G系统才能工作。在设计过程中,我们需要反复评估系统可靠性。当系统规模较小或中等时,使用通用生成功能(UGF)方法。当系统规模较大时,将使用递归方法,这种方法效率更高。制定了两个最佳模型。一种是在保证系统可靠性高于预定值的同时使预期的总成本最小化。另一个是在限制总系统成本的情况下最大化系统可靠性。遗传算法(GA)和禁忌搜索(TS)方法都用于解决所提出的优化模型。由于良好的TS算法的关键通常是针对特定问题的策略和内存结构,因此没有现有的通用TS工具可用。因此,本文讨论的TS方法比GA方法要详细得多。比较用这两种方法获得的结果。结果表明,这两种方法都是解决此类问题的有力工具。但是,TS在计算方面比GA更有效。本文的材料已于19发表。

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