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Redundancy allocation with non-identical component and uncertainty

Authors: Jianyu Zhao; Shengkui Zeng; Jianbin Guo; Chunbo Yang;

Redundancy allocation with non-identical component and uncertainty

Abstract

Redundancy allocation has been widely used in many fields to enhance system reliability. In practice, it is essential to take component reliability uncertainties into consideration and find smart configuration for system design. In this article, a redundancy allocation problem for k-out-of-n series-parallel system is employed, and the optimization problem considering interval valued uncertainty and non-identical component mixing is presented. The Min-Max regret and the coefficient of deviation are respectively introduced to improve existing order relation criterion for interval analysis and two associated optimization models are established. The general objective is to obtain high system reliability with small deviation. Then, an appropriate genetic algorithm based on the characteristic of proposed models is developed. Finally, several numerical cases are conducted to demonstrate the validity and efficiency of proposed approach. This work may contribute to more flexible design for redundancy allocation.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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