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Performance evaluation of a transportation-type bulk queue with generally distributed inter-arrival times

机译:具有普遍分布的到达时间的运输型散装队列的性能评估

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This paper is motivated by the performance evaluation of circulating vertical conveyor systems (CVCSs). CVCSs are bulk queues of transportation type. These material handling systems feature generally distributed inter-arrival times, which can be longer than the bulk service time. This leads to interdependencies between the number of arrivals in consecutive service intervals and the number of loads in the queue. We propose a new discrete-time approach for the steady-state analysis of such bulk service queues of transportation type with general arrival and service processes and finite server and limited queue capacities. The approach is based on a finite Markov chain that generates complete probability distributions for the key performance measures, including the queue length, waiting time and departing batch size. The proposed approach is exact in the cases of discrete-time slots, e.g. as in communication systems. We investigate the discretisation error that arises if the approach is used as an approximation for the continuous time using a numerical comparison to a discrete-event simulation. Moreover, we examine the impact of arrival stream variability on the system performance and compare the positive effects of a higher frequency of server visits with the effects arising from larger pickup capacities.
机译:本文受循环垂直输送机系统(CVCS)性能评估的启发。 CVCS是运输类型的大宗队列。这些物料搬运系统通常具有到达时间的分布时间,该时间可以比批量服务时间更长。这导致连续服务间隔中的到达数量与队列中的负载数量之间存在相互依赖性。我们提出了一种新的离散时间方法,用于这种类型的具有一般到达和服务过程以及有限的服务器和有限的队列容量的运输类型的大容量服务队列的稳态分析。该方法基于有限的马尔可夫链,该链为关键绩效指标生成完整的概率分布,包括队列长度,等待时间和出发批次大小。所提出的方法在离散时隙的情况下是准确的,例如如在通信系统中。我们使用离散事件模拟的数值比较来研究将方法用作连续时间的近似值时出现的离散化误差。此外,我们检查了到达流可变性对系统性能的影响,并比较了较高的服务器访问频率与较大的接机容量所产生的影响。

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