Computing the reliability of a stochastic distribution network subject to budget constraint

•A (d, b)-minimal path method is developed to compute the reliability index R(d,b).•A modified model is constructed to search for (d, b)-minimal paths.•A novel and fast technique is devised to identify duplicate (d, b)-MPs.•The developed method indicates distinct advantages over the existing ones. R...

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Published inReliability engineering & system safety Vol. 216; p. 107947
Main Authors Xu, Xiu-Zhen, Niu, Yi-Feng, Song, Yi-Fan
Format Journal Article
LanguageEnglish
Published Barking Elsevier Ltd 01.12.2021
Elsevier BV
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Summary:•A (d, b)-minimal path method is developed to compute the reliability index R(d,b).•A modified model is constructed to search for (d, b)-minimal paths.•A novel and fast technique is devised to identify duplicate (d, b)-MPs.•The developed method indicates distinct advantages over the existing ones. Reliability and delivery cost are two crucial indicators to show whether a distribution network is in the stable and high-quality operation. This paper develops a (d, b)-minimal path ((d, b)-MP) based algorithm to compute the reliability R(d,b) of a stochastic distribution network as the probability that a prescribed demand d can be successfully delivered from the source to the destination subject to the constraint that the total delivery cost is not above b. Specifically, this paper focuses two aspects to facilitate the solution of (d, b)-MPs. Firstly, by transforming a large Diophantine system into several small Diophantine systems, a modified model is constructed to promote the efficiency of searching for (d, b)-MP candidates and narrow the scope of duplicate (d, b)-MPs. Secondly, a novel technique is devised to identify all duplicate (d, b)-MPs, and its efficiency advantage is theoretically proven. Finally, it is demonstrated through numerical experiments that the developed algorithm compares favorably with the existing ones in the literature, and a case study is provided to display the application of the algorithm.
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ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2021.107947