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Link l is failed in that replication: (j ) Xl = 1, j = k; Xl(k) = 0, if k L/Nl endFor endFor Initialize T = 0 For i from 1 to L Count replications corresponding to an operational state of the network: T = T + (X(i) ) endFor Return R = T /L The complexity analysis of this algorithm, given in [30], shows that the execution time per sample has worst-case complexity O(|E|), as in the case of crude Monte Carlo Nevertheless, as the number of random variables that are needed in the dagger method is much smaller than in the crude Monte Carlo, there may be a large gain in execution time, which is an important advantage of the method compared to the crude procedure The variance reduction obtained by the dagger method is based on the induced negative correlation among the samples which belong to the same sub-block for some link of the network, and is relatively small, approaching 0 when the link reliability is near 1 El Khadiri and Rubino [27] discuss some problems of the dagger method, which happen in particular when value L is too large As it is necessary to generate and save into memory L states of the network, memory requirements grow linearly with L The authors show that the block size L may be chosen arbitrarily, and they propose an alternative method, inspired by the dagger and applying a generalization of the standard antithetic approach This new method obtains better results, both because L can be chosen arbitrarily, and because the sampling algorithm used incorporates some features in order to improve its ef ciency The algorithm employs mechanisms similar to those used in discrete event simulation, employing a list with the incumbent failure instants for each link, and nding which is the rst replication including at least one failure This implementation yields important gains in execution time and also results in minimal memory complexity (which depends linearly on the network size and is independent of L) When all links have the same reliability p, the generalized antithetic algorithm has sample complexity O |E|), where = max(1/L, 1 p) This represents an improvement over the crude method which grows with the block size L, up to a bound given by the inverse of the link reliabilities (in the worst case, p = 05, we have that the maximum gain that can be attained is a factor of 2, corresponding to setting L = 2). how to create barcodes in excel 2010 free How to insert barcode into cells easily with barcode font in Excel ?
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