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An effective algorithm for computing all‐terminal reliability bounds

Authors: Jaime Silva; Teresa Gomes; David Tipper; Lúcia Martins; Velin Kounev;

An effective algorithm for computing all‐terminal reliability bounds

Abstract

The exact calculation of all‐terminal reliability is not feasible in large networks. Hence estimation techniques and lower and upper bounds for all‐terminal reliability have been utilized. Here, we propose using an ordered subset of the mincuts and an ordered subset of the minpaths to calculate an all‐terminal reliability upper and lower bound, respectively. The advantage of the proposed new approach results from the fact that it does not require the enumeration of all mincuts or all minpaths as required by other bounds. The proposed algorithm uses maximally disjoint minpaths, prior to their sequential generation, and also uses a binary decision diagram for the calculation of their union probability. The numerical results show that the proposed approach is computationally feasible, reasonably accurate and much faster than the previous version of the algorithm. This allows one to obtain tight bounds when it not possible to enumerate all mincuts or all minpaths as revealed by extensive tests on real‐world networks. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 282–295 2015

Country
Portugal
Keywords

binary decision diagram (BDD), all-terminal network reliability, sum of disjoint products, bounds computation, network availability

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
23
Top 10%
Top 10%
Top 10%
Green
hybrid