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Discrete vs. Continuous Simulation: When Does It Matter?

机译:离散与连续仿真:什么时候起作用?

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The purpose of this study is to illustrate the similarities and differences between discrete event simulation and continuous simulation modeling. A simple M/M/2 queuing system with crowd-dependent arrival rate is used. In the first part, the arrival rate decreases immediately as the number of customers in the system increases. The system is modeled using discrete event and continuous simulation. The results of two simulations are compared with each other and with their analytical solutions. In the second part, the number of customers in the system affects the arrival rate first with a continuous information delay, then with a discrete delay. Discrete and continuous simulations give very similar results in terms of dynamic behaviors of system variables. There are some minor differences in terms of the steady-state values of the variables, particularly the average time spent in system. Finally, increasing proportionately all parameters of the system (arrival rate and number of servers), reduces the discreteness of the system, bringing the discrete and continuous simulation results much closer.
机译:本研究的目的是说明离散事件仿真和连续仿真建模之间的异同。使用了一个简单的M / M / 2排队系统,该系统具有取决于人群的到达率。在第一部分中,到达率随系统中客户数量的增加而立即降低。该系统使用离散事件和连续仿真进行建模。将两个模拟的结果相互比较,并与它们的解析解进行比较。在第二部分中,系统中的客户数量首先以连续的信息延迟,然后以离散的延迟来影响到达率。就系统变量的动态行为而言,离散和连续仿真得出的结果非常相似。在变量的稳态值方面,尤其是在系统上花费的平均时间方面,存在一些细微的差异。最后,按比例增加系统的所有参数(到达率和服务器数量),减少了系统的离散性,使离散和连续的仿真结果更加接近。

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