具有级别依赖到达和灾难的单服务器队列增广截断近似的数值实现

Q4 Decision Sciences
Masatoshi Kimura, T. Takine
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引用次数: 0

摘要

本文考虑了具有级别相关到达和灾难的单服务器队列中平稳队列长度分布的计算。我们假设服务时间遵循一般分布,因此,我们通过嵌入马尔可夫链来考虑平稳队列长度分布。由于这种嵌入的马尔可夫链具有无限多个状态、级别依赖性和级别的双向跳跃,因此很难精确计算全局平衡方程的解。因此,我们考虑了增广截断近似。特别地,我们关注嵌入马尔可夫链的截断状态转移概率矩阵的计算,假设在服务时间内底层的连续时间吸收马尔可夫链是不可均匀的。在某些稳定性条件下,我们发展了截断转移概率矩阵的计算过程,其中由于截断引起的误差的上界可以预先设置。我们还提供了一些数值例子,并证明我们的程序运行良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NUMERICAL IMPLEMENTATION OF THE AUGMENTED TRUNCATION APPROXIMATION TO SINGLE-SERVER QUEUES WITH LEVEL-DEPENDENT ARRIVALS AND DISASTERS
This paper considers the computation of the stationary queue length distribution in singleserver queues with level-dependent arrivals and disasters. We assume that service times follow a general distribution and therefore, we consider the stationary queue length distribution via an imbedded Markov chain. Because this imbedded Markov chain has infinitely many states, level dependence, and bidirectional jumps of levels, it is hard to compute the solution of the global balance equation exactly. We thus consider the augmented truncation approximation. In particular, we focus on the computation of the truncated state transition probability matrix of the imbedded Markov chain, assuming that the underlying continuous-time absorbing Markov chain during a service time is not uniformizable. Under some stability conditions, we develop a computational procedure for the truncated transition probability matrix, where the upper bound of errors owing to truncation can be set in advance. We also provide some numerical examples and demonstrate that our procedure works well.
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来源期刊
Journal of the Operations Research Society of Japan
Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学
CiteScore
0.70
自引率
0.00%
发文量
12
审稿时长
12 months
期刊介绍: The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.
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