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Development of computational algorithm for multiserver queue with renewal input and synchronous vacation

机译:具有更新输入和同步休假的多服务器队列计算算法的开发

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In this paper, we develop a new computational algorithm for calculating the Markov chain stationary distribution based on a Taylor series approach, where the Taylor series coefficients are expressed in closed-form in terms of the fundamental matrix of the underlying Markov chain. Additionally, we provide an approximate expression for the remainder term of the Taylor series that can be computed in an efficient manner. Specifically, we demonstrate the application of the proposed framework in analyzing a multi-server queueing system with synchronous vacation. The only required assumption of the proposed framework is that the entries of the transition matrix are differentiable functions with respect to a control parameter. Numerical examples are sketched out to illustrate the accuracy of the proposed method.
机译:在本文中,我们开发了一种新的计算算法,该算法基于泰勒级数方法来计算马尔可夫链的平稳分布,其中泰勒级数系数根据基础马尔可夫链的基本矩阵以闭合形式表示。此外,我们提供了泰勒级数余项的近似表达式,可以有效地进行计算。具体来说,我们演示了所提出的框架在分析具有同步休假的多服务器排队系统中的应用。所提出的框架的唯一需要的假设是,转换矩阵的项是相对于控制参数的可微函数。数值例子被勾勒出来,以说明所提方法的准确性。

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