论文标题
用延迟信息打破队列中的对称性
Breaking the Symmetry in Queues with Delayed Information
论文作者
论文摘要
为客户提供有关服务系统的队列长度信息有可能影响客户加入队列的决定。因此,排队系统的经理必须了解其提供的信息将如何影响系统的性能。为此,我们构建和分析了一个二维确定性流体模型,该模型结合了基于延迟的队列长度信息的客户选择行为。所有以前的文献都假设所有队列都具有相同的参数,而潜在的动力学系统是对称的。但是,在本文中,我们通过允许每个队列的到达速率,服务率和选择模型参数不同而放宽了这种对称性假设。我们的方法学利用了多个量表和渐近分析的方法,以了解如何打破对称性。我们发现,不对称性可以对排队系统的基本动力产生很大的影响。
Giving customers queue length information about a service system has the potential to influence the decision of a customer to join a queue. Thus, it is imperative for managers of queueing systems to understand how the information that they provide will affect the performance of the system. To this end, we construct and analyze a two-dimensional deterministic fluid model that incorporates customer choice behavior based on delayed queue length information. All of the previous literature assumes that all queues have identical parameters and the underlying dynamical system is symmetric. However, in this paper, we relax this symmetry assumption by allowing the arrival rates, service rates, and the choice model parameters to be different for each queue. Our methodology exploits the method of multiple scales and asymptotic analysis to understand how to break the symmetry. We find that the asymmetry can have a large impact on the underlying dynamics of the queueing system.