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首页> 外文期刊>Journal of simulation >Queuing systems in a feedback environment: Continuous versus discrete-event simulation
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Queuing systems in a feedback environment: Continuous versus discrete-event simulation

机译：反馈环境中的排队系统：连续与离散事件模拟

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The discrete stochastic nature of typical queuing problems calls for discrete-event simulation, rather than continuous simulation that would ignore the discrete details that may be important in queuing dynamics. However, continuous simulation can perhaps be suitable for certain large queuing systems that involve feedback interactions and time delays. This study examines this question by a series of simulation experiments with queuing systems. We start with an M/M/2 system with state-dependent arrivals. Since continuous simulation represents the system states by continuous variables, when these variables (number of entities) revolve around small integer values, discrete and continuous simulation approaches exhibit significant differences in their output dynamics. However, when the system scale is increased (many servers, many entities), errors caused by continuity assumption drop significantly and the two simulation approaches yield much closer outputs. Finally, when a delay is introduced before the state of the system influences the arrival rates, the system behaviour becomes oscillatory, involving even sustained oscillations when the delay is discrete. We show that in such settings, continuous simulation can be superior to discrete simulation, since the system exhibits far-from-equilibrium dynamics driven by the endogenous system structure, rather than by discrete stochastic events. Our results have various real-life modelling implications.
机译：典型排队问题的离散随机性质要求进行离散事件模拟，而不是连续模拟，而连续模拟会忽略对动态排队可能很重要的离散细节。但是，连续模拟可能适用于某些涉及反馈交互和时间延迟的大型排队系统。这项研究通过一系列使用排队系统的模拟实验来研究这个问题。我们从具有状态相关到达的M / M / 2系统开始。由于连续模拟通过连续变量表示系统状态，因此当这些变量（实体数）围绕小整数值旋转时，离散和连续模拟方法的输出动力学会表现出显着差异。但是，当系统规模增加（许多服务器，许多实体）时，由连续性假设引起的错误将大大降低，并且两种仿真方法都将产生更接近的输出。最终，当在系统状态影响到达速率之前引入延迟时，系统行为变得振荡，当延迟是离散的时，甚至会持续振荡。我们表明，在这种情况下，连续仿真可能优于离散仿真，因为系统展现出的远非平衡动力学是由内源系统结构驱动的，而不是由离散随机事件驱动的。我们的结果具有各种现实生活中的建模含义。

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