Efficient Estimation of Stochastic Flow Network Reliability | Zendy

Héctor Cancela | Zendy; Leslie Murray | Zendy; Gerardo Rubino | Zendy

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Efficient Estimation of Stochastic Flow Network Reliability

Author(s) -

Héctor Cancela,

Leslie Murray,

Gerardo Rubino

Publication year - 2019

Publication title -

ieee transactions on reliability

Language(s) - English

Resource type - Journals

eISSN - 1558-1721

pISSN - 0018-9529

DOI - 10.1109/tr.2019.2897322

Subject(s) - reliability (semiconductor) , computer science , basis (linear algebra) , process (computing) , variance (accounting) , reduction (mathematics) , flow network , stochastic process , algorithm , mathematical optimization , reliability engineering , mathematics , engineering , statistics , power (physics) , physics , geometry , accounting , quantum mechanics , business , operating system

The Creation Process is an algorithm that transforms a static network model into a dynamic one. It is the basis of different variance reduction methods designed to make efficient reliability estimations on highly reliable networks in which links can only assume two possible values, operational or failed. In this paper, the Creation Process is extended to let it operate on network models in which links can assume more than two values. The proposed algorithm, called here as the Multilevel Creation Process, is the basis of a method, also introduced here, to make efficient reliability estimations of highly reliable stochastic flow networks. The method proposed, which consists in an application of Splitting over the Multilevel Creation Process, is empirically shown to be accurate, efficient, and robust.

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