TY - JOUR

T1 - On the marshall-olkin copula model for network reliability under dependent failures

AU - Matus, Omar

AU - Barrera, Javiera

AU - Moreno, Eduardo

AU - Rubino, Gerardo

N1 - Publisher Copyright:
© 1963-2012 IEEE.

PY - 2019/6

Y1 - 2019/6

N2 - The Marshall-Olkin (MO) copula model has emerged as the standard tool for capturing dependence between components in failure analysis in reliability. In this model, shocks arise at exponential random times, that affect one or several components inducing a natural correlation in the failure process. However, because the number of parameter of the model grows exponentially with the number of components, MO suffers of the 'curse of dimensionality.' MO models are usually intended to be applied to design a network before its construction; therefore, it is natural to assume that only partial information about failure behavior can be gathered, mostly from similar existing networks. To construct such an MO model, we propose an optimization approach to define the shock's parameters in the MO copula, in order to match marginal failures probabilities and correlations between these failures. To deal with the exponential number of parameters of this problem, we use a column-generation technique. We also discuss additional criteria that can be incorporated to obtain a suitable model. Our computational experiments show that the resulting MO model produces a close estimation of the network reliability, especially when the correlation between component failures is significant.

AB - The Marshall-Olkin (MO) copula model has emerged as the standard tool for capturing dependence between components in failure analysis in reliability. In this model, shocks arise at exponential random times, that affect one or several components inducing a natural correlation in the failure process. However, because the number of parameter of the model grows exponentially with the number of components, MO suffers of the 'curse of dimensionality.' MO models are usually intended to be applied to design a network before its construction; therefore, it is natural to assume that only partial information about failure behavior can be gathered, mostly from similar existing networks. To construct such an MO model, we propose an optimization approach to define the shock's parameters in the MO copula, in order to match marginal failures probabilities and correlations between these failures. To deal with the exponential number of parameters of this problem, we use a column-generation technique. We also discuss additional criteria that can be incorporated to obtain a suitable model. Our computational experiments show that the resulting MO model produces a close estimation of the network reliability, especially when the correlation between component failures is significant.

KW - Copula theory

KW - failure analysis

KW - network design

KW - optimization methods

KW - reliability

UR - http://www.scopus.com/inward/record.url?scp=85053286165&partnerID=8YFLogxK

U2 - 10.1109/TR.2018.2865707

DO - 10.1109/TR.2018.2865707

M3 - Article

AN - SCOPUS:85053286165

SN - 0018-9529

VL - 68

SP - 451

EP - 461

JO - IEEE Transactions on Reliability

JF - IEEE Transactions on Reliability

IS - 2

M1 - 8464101

ER -