【24h】

Fast solvers for queueing systems with negative customers

机译:具有负客户的排队系统的快速求解器

获取原文
获取原文并翻译 | 示例

摘要

In this paper, we are interested in solving queueing systems having Poisson batch arrivals, exponential servers and negative customers. Preconditioned Conjugate Gradient (PCG) method is applied to solving the steady-state probability distribution of the queueing system. Preconditioners are constructed by exploiting near-Toeplitz structure of the generator matrix and the Gohberg-Semumcul formula. We proved that the preconditioned system has singular values clustered around one. Therefore Conjugate Gradient (CG) methods when applied to solving the preconditioned system, we expect fast convergence rate. Numerical examples are given to demonstrate our claim.
机译:在本文中,我们对解决具有Poisson批次到达,指数服务器和负客户的排队系统感兴趣。预处理共轭梯度法(PCG)被用于求解排队系统的稳态概率分布。通过利用生成器矩阵的近Toeplitz结构和Gohberg-Semumcul公式构造预处理器。我们证明了预处理系统的奇异值聚集在一个附近。因此,当将共轭梯度(CG)方法用于求解预处理系统时,我们期望快速收敛。数值例子说明了我们的主张。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号