STAFFING A SERVICE SYSTEM WITH NON-POISSON NON-STATIONARY ARRIVALS
STAFFING A SERVICE SYSTEM WITH NON-POISSON NON-STATIONARY ARRIVALS
复制标题
为服务系统配备非泊松非平稳到达
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
W. Whitt
中科院分区：
文献类型：
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作者：
Beixiang He;Yunan Liu;W. Whitt
在服务系统到达数据中发现的非泊松随机变化的动机，我们扩展了已建立的服务系统人员配备算法的平方根人员配备公式，允许非泊松到达过程。我们开发了一个一般模型的非泊松非平稳到达过程，其中包括作为一个特殊情况下的非平稳考克斯过程（修改的泊松过程中，其速率本身是一个非平稳随机过程），这已在文献中提倡。我们的非泊松随机变异性的影响，通过繁忙的交通限制的峰值（在相关的固定无限服务器排队模型中的方差与平均值的比值），这取决于到达过程中通过其中心极限定理的行为上的人员配备。我们提供了简单的公式来量化的非泊松到达后的人员配置决策的性能影响，以达到预期的服务水平。我们进行仿真实验与非平稳马尔可夫调制泊松到达过程与正弦到达率函数证明，人员配备算法是有效的稳定在指定目标的时变概率延迟。
Motivated by non-Poisson stochastic variability found in service system arrival data, we extend established service system staffing algorithms using the square-root staffing formula to allow for non-Poisson arrival processes. We develop a general model of the non-Poisson non-stationary arrival process that includes as a special case the non-stationary Cox process (a modification of a Poisson process in which the rate itself is a non-stationary stochastic process), which has been advocated in the literature. We characterize the impact of the non-Poisson stochastic variability upon the staffing through the heavy-traffic limit of the peakedness (ratio of the variance to the mean in an associated stationary infinite-server queueing model), which depends on the arrival process through its central limit theorem behavior. We provide simple formulas to quantify the performance impact of the non-Poisson arrivals upon the staffing decisions, in order to achieve the desired service level. We conduct simulation experiments with non-stationary Markov-modulated Poisson arrival processes with sinusoidal arrival rate functions to demonstrate that the staffing algorithm is effective in stabilizing the time-varying probability of delay at designated targets.
随着到达时间和客户反馈的变化，稳定服务系统的性能
影响因子：
6.4
作者：
Liu, Yunan;Whitt, Ward
通讯作者：
Whitt, Ward