Abstract
In this study, simulation approaches for the reliability estimation of a multi-state network (MSN) are developed; the approaches obviate the reliance on known capacity probability distributions. Two procedures are proposed to randomly generate the system (capacity) state, which is further compared with the lower bounds of demand, for estimating system reliability. In particular, the simulation approaches consider the time-varying reliability function for components in the MSN. Two examples, i.e., with and without considering time-varying reliability functions, are investigated to determine the effectiveness (accuracy, convergence, and variance) and efficiency of the proposed procedures. Additionally, a practical case of the National Science Foundation Network is investigated to validate the scalability and applicability of the proposed procedures. Experimental results show that both proposed procedures are effective and efficient for estimating the system reliability of an MSN.
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