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Correction to: A sequential update algorithm for computing the stationary distribution vector in upper block-Hessenberg Markov chains

机译:校正:一种顺序更新算法,用于计算上块 - Hessenberg Markov链条的固定分布向量

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摘要

This paper proposes a new algorithm for computing the stationary distribution vector in continuous-time upper block-Hessenberg Markov chains. To this end, we consider the last-block-column-linearly-augmented (LBCL-augmented) truncation of the (infinitesimal) generator of the upper block-Hessenberg Markov chain. The LBCL-augmented truncation is a linearly augmented truncation such that the augmentation distribution has its probability mass only on the last block column. We first derive an upper bound for the total variation distance between the respective stationary distribution vectors of the original generator and its LBCL-augmented truncation. Based on the upper bound, we then establish a series of linear fractional programming (LFP) problems to obtain augmentation distribution vectors such that the bound converges to zero. Using the optimal solutions of the LFP problems, we construct a matrix-infinite-product (MIP) form of the original (i.e., not approximate) stationary distribution vector and develop a sequential update algorithm for computing the MIP form. Finally, we demonstrate the applicability of our algorithm to BMAP/M/ queues and M/M/s retrial queues.
机译:本文提出了一种用于计算连续时间上块 - Hessenberg Markov链条的固定分布向量的新算法。为此,我们考虑上块Hessenberg Markov链条(Infiniteimal)发生器的最后块列线性增强(LBCL-Augmented)截断。 LBCL-Augmented截断是线性增强截断,使得增强分布仅在最后一块块列上具有其概率质量。我们首先导出原始发生器的各个固定分配矢量与其LBCL增强截断之间的总变化距离的上限。基于上限,我们建立了一系列线性分数编程(LFP)问题以获得增强分配矢量,使得绑定到零。利用LFP问题的最佳解决方案,我们构建原始(即,非近似)静止分布向量的矩阵无限产品(MIP)形式,并开发用于计算MIP形式的顺序更新算法。最后,我们展示了算法对BMAP / M /队列和M / M / S回重队列的适用性。

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