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Título: | Separability in Stochastic Binary Systems |
Autor: | Guerberoff, Gustavo Robledo, Franco Romero, Pablo Stábile, Luis |
Tipo: | Artículo |
Palabras clave: | Stochastic Binary System (SBS), P-Hard computational problems |
Fecha de publicación: | 2018 |
Resumen: | A Stochastic Binary System (SBS) is a
mathematical model of multi-component on-off systems subject
to random failures. SBS models extend classical network
reliability models (where the components subject to failure are
nodes or links of a graph) and are able to represent more
complex interactions between the states of the individual
components and the operation of the system under study.
The reliability evaluation of stochastic binary systems
belongs to the class of NP-Hard computational problems.
Furthermore, the number of states is exponential with respect
to the size of the system (measured in the number of
components). As a consequence, the representation of an SBS
becomes a key element in order to develop exact and/or
approximation methods for reliability evaluation.
The contributions of this paper are three-fold. First, we
present the concept of separable stochastic binary systems,
showing key properties, such as an efficient representation and
complexity in the reliability evaluation. Second, we fully
characterize separable systems in two ways, using a geometrical
interpretation and minimum-cost operational subsystems.
Finally, we show the application of separable systems in
network reliability models, specifically in the all-terminal
reliability model, which has a wide spectrum of applications.
Index Terms—Stochastic Binary System, Network Reliability,
Computational Complexity, Chernoff Inequality. |
Editorial: | Udelar. FI |
Citación: | Guerberoff, G., Robledo, F., Romero, P. y Stábile, L. "Separability in Stochastic Binary Systems" [en línea] Udelar.FI, 2018. |
Aparece en las colecciones: | Publicaciones académicas y científicas - Facultad de Ingeniería |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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Separability.pdf | 377,36 kB | Adobe PDF | Visualizar/Abrir |
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