确定非固定到达和正常服务时间的呼叫中心中继线

Siddharth Mahajan
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摘要

呼叫中心的两个重要资源是员工数量和所需的中继线路数量。在本文中,我们重点讨论了呼叫中心应该拥有的中继线路数量的决定。目前的做法是使用Erlang B或M/M/s/0排队模型,该模型假设泊松到达,指数服务时间,s服务器和队列中没有位置,即没有客户可以等待。在本文中,我们通过包括呼叫中心中存在的两个现实特征,改进了确定所需中继线数的实践状态。第一个现实特征是考虑到达的非平稳性。第二个特点是考虑对数正态服务时间分布,而不是指数分布。这两个特征都有广泛的经验证据。为了进行我们的计算,我们使用了Massey和Whitt的一篇论文的结果,运筹学,44(6),1996。我们有两个主要发现。首先,我们在数值上发现,在我们的非平稳Erlang损失模型Mt/G/s/0中,不敏感的结果是成立的。到达呼叫中心的阻塞概率仅取决于对数正态服务时间分布的平均值,而不取决于其方差。我们的第二个发现是,目前的做法相当稳健。特别地,我们使用平稳泊松近似找到所需干线的数目。这个近似假设平稳泊松到达具有适当选择的到达率和指数服务时间。这个近似值在预测所需干线的数量方面做得很好。
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Determining Trunk Lines in Call Centers with Nonstationary Arrivals and Lognormal Service Times
Two important resources in a call center are the number of staff and the number of trunk lines required. In this paper, we focus on the decision of the number of trunk lines that a call center should have. The current practice is to use the Erlang B or the M/M/s/0 queueing model which assumes Poisson arrivals, exponential service times, s servers and no places in queue, i.e. no customers can wait. In this paper, we improve on the state of practice in determining the required number of trunk lines, by including two realistic features present in call centers. The first realistic feature is to consider nonstationarity of arrivals. The second feature is to consider the lognormal service time distribution instead of the exponential distribution. There is extensive empirical evidence for both features. In order to carry out our computations we use the results of a paper by Massey and Whitt, Operations Research, 44(6), 1996. We have two main findings. Firstly, we find numerically that in our nonstationary Erlang loss model, Mt/G/s/0, an insensitivity result holds. The blocking probability of arrivals at the call center depends only on the mean of the lognormal service time distribution and not on its variance. Our second finding is that current practice is quite robust. In particular, we find the number of trunk lines required using a stationary Poisson approximation. This approximation assumes stationary Poisson arrivals with an appropriately chosen arrival rate and exponential service times. The approximation does quite well in predicting the number of trunk lines required.
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