On the Reliability Estimation of Stochastic Binary System
A stochastic binary system is a multi-component on-off system subject to random independent failures on its components. After potential failures, the state of the subsystem is ruled by a logical function (called structure function) that determines whether the system is operational or not. Stochastic...
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| Other Authors: | , , , |
| Format: | article |
| Language: | English |
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2021
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| Online Access: | https://hdl.handle.net/20.500.12381/645 |
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| _version_ | 1868890087602782208 |
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| author | Cancela, Héctor |
| author2 | Murray, Leslie Robledo, Franco Romero, Pablo Sartor, Pablo |
| author2_role | author author author author |
| author_browse | Cancela, Héctor Murray, Leslie Robledo, Franco Romero, Pablo Sartor, Pablo |
| author_facet | Cancela, Héctor Murray, Leslie Robledo, Franco Romero, Pablo Sartor, Pablo |
| author_role | author |
| collection | REDI |
| dc.creator.none.fl_str_mv | Cancela, Héctor Murray, Leslie Robledo, Franco Romero, Pablo Sartor, Pablo |
| dc.date.none.fl_str_mv | 2021 2022-10-17T13:33:01Z 2022-10-17T13:33:01Z |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/20.500.12381/645 FCE_1_2019_1_156693 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Wiley |
| dc.relation.none.fl_str_mv | https://doi.org/10.1111/itor.13034 |
| dc.rights.none.fl_str_mv | Acceso abierto info:eu-repo/semantics/openAccess Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND) |
| dc.source.none.fl_str_mv | International Transactions in Operations Research reponame:REDI instname:Agencia Nacional de Investigación e Innovación instacron:Agencia Nacional de Investigación e Innovación |
| dc.subject.none.fl_str_mv | System Reliability Stochastic Binary Systems Permutation Monte Carlo Splitting Duality Ciencias Naturales y Exactas Ciencias de la Computación e Información Matemáticas Estadística y Probabilidad |
| dc.title.none.fl_str_mv | On the Reliability Estimation of Stochastic Binary System |
| dc.type.none.fl_str_mv | Artículo info:eu-repo/semantics/article Enviado info:eu-repo/semantics/submittedVersion |
| description | A stochastic binary system is a multi-component on-off system subject to random independent failures on its components. After potential failures, the state of the subsystem is ruled by a logical function (called structure function) that determines whether the system is operational or not. Stochastic binary systems (SBS) serve as a natural generalization of network reliability analysis, where the goal is to find the probability of correct operation of the system (in terms of connectivity, network diameter or different measures of success). A particular subclass of interest is stochastic monotone binary systems (SMBS), which are characterized by non-decreasing structure. We explore the combinatorics of SBS, which provide building blocks for system reliability estimation, looking at minimal non-operational subsystems, called mincuts. One key concept to understand the underlying combinatorics of SBS is duality. As methods for exact evaluation take exponential time, we discuss the use of Monte Carlo algorithms. In particular, we discuss the F-Monte Carlo method for estimating the reliability polynomial for homogeneous SBS, the Recursive Variance Reduction (RVR) for SMBS, which builds upon the efficient determination of mincuts, and three additional methods that combine in different ways the well--known techniques of Permutation Monte Carlo and Splitting. These last three methods are based on a stochastic process called Creation Process, a temporal evolution of the SBS which is static by definition. All the methods are compared using different topologies, showing large efficiency gains over the basic Monte Carlo scheme. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | anni_6bb9dfa079514be708db077419daa6ea |
| identifier_str_mv | FCE_1_2019_1_156693 |
| instacron_str | Agencia Nacional de Investigación e Innovación |
| institution | Agencia Nacional de Investigación e Innovación |
| instname_str | Agencia Nacional de Investigación e Innovación |
| language | eng |
| network_acronym_str | anni |
| network_name_str | oai-lr-anni |
| oai_identifier_str | oai:redi.anii.org.uy:20.500.12381/645 |
| publishDate | 2021 |
| publishDateSort | 2021 |
| publisher.none.fl_str_mv | Wiley |
| reponame_str | REDI |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | Acceso abierto Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND) |
| spelling | On the Reliability Estimation of Stochastic Binary SystemCancela, HéctorMurray, LeslieRobledo, FrancoRomero, PabloSartor, PabloSystem ReliabilityStochastic Binary SystemsPermutation Monte CarloSplittingDualityCiencias Naturales y ExactasCiencias de la Computación e InformaciónMatemáticasEstadística y ProbabilidadA stochastic binary system is a multi-component on-off system subject to random independent failures on its components. After potential failures, the state of the subsystem is ruled by a logical function (called structure function) that determines whether the system is operational or not. Stochastic binary systems (SBS) serve as a natural generalization of network reliability analysis, where the goal is to find the probability of correct operation of the system (in terms of connectivity, network diameter or different measures of success). A particular subclass of interest is stochastic monotone binary systems (SMBS), which are characterized by non-decreasing structure. We explore the combinatorics of SBS, which provide building blocks for system reliability estimation, looking at minimal non-operational subsystems, called mincuts. One key concept to understand the underlying combinatorics of SBS is duality. As methods for exact evaluation take exponential time, we discuss the use of Monte Carlo algorithms. In particular, we discuss the F-Monte Carlo method for estimating the reliability polynomial for homogeneous SBS, the Recursive Variance Reduction (RVR) for SMBS, which builds upon the efficient determination of mincuts, and three additional methods that combine in different ways the well--known techniques of Permutation Monte Carlo and Splitting. These last three methods are based on a stochastic process called Creation Process, a temporal evolution of the SBS which is static by definition. All the methods are compared using different topologies, showing large efficiency gains over the basic Monte Carlo scheme.Agencia Nacional de Investigación e InnovaciónMath-AMSUDWiley2022-10-17T13:33:01Z2022-10-17T13:33:01Z2021Artículoinfo:eu-repo/semantics/articleEnviadoinfo:eu-repo/semantics/submittedVersionhttps://hdl.handle.net/20.500.12381/645FCE_1_2019_1_156693International Transactions in Operations Researchreponame:REDIinstname:Agencia Nacional de Investigación e Innovacióninstacron:Agencia Nacional de Investigación e Innovaciónenghttps://doi.org/10.1111/itor.13034Acceso abiertoinfo:eu-repo/semantics/openAccessReconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)oai:redi.anii.org.uy:20.500.12381/6452026-06-16T05:01:43Z |
| spellingShingle | On the Reliability Estimation of Stochastic Binary System Cancela, Héctor System Reliability Stochastic Binary Systems Permutation Monte Carlo Splitting Duality Ciencias Naturales y Exactas Ciencias de la Computación e Información Matemáticas Estadística y Probabilidad |
| status_str | submittedVersion |
| title | On the Reliability Estimation of Stochastic Binary System |
| title_full | On the Reliability Estimation of Stochastic Binary System |
| title_fullStr | On the Reliability Estimation of Stochastic Binary System |
| title_full_unstemmed | On the Reliability Estimation of Stochastic Binary System |
| title_short | On the Reliability Estimation of Stochastic Binary System |
| title_sort | On the Reliability Estimation of Stochastic Binary System |
| topic | System Reliability Stochastic Binary Systems Permutation Monte Carlo Splitting Duality Ciencias Naturales y Exactas Ciencias de la Computación e Información Matemáticas Estadística y Probabilidad |
| url | https://hdl.handle.net/20.500.12381/645 |