The Effect of Correlated Arrivals on Queues

Patuwo, B. Eddy; Disney, Ralph L.; Mcnickle, Donald

doi:10.1080/07408179308964296

Cited by 49 publications

(17 citation statements)

References 10 publications

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“…However, the autocorrelation of demand has never been researched. As Livny et al (1993) and Patuwo et al (1993) claim, it is an important factor a ecting the performance of queuing systems. Most queuing models assume independent customer arrivals, however, those models are often poor representations of real-life systems where correlations do, in fact, abound.…”

Section: Introductionmentioning

confidence: 99%

The effect of autocorrelated demand in JIT production systems

Takahashi¹,

Nakamura²

1998

International Journal of Production Research

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As a system of production planning and inventory control for multi-stage production inventory systems, this paper deals with the Kanban system in the just-intime (JIT) concept. In this paper, the autocorrelation of demand is considered as an important factor a ecting the performance of the Kanban system. Mathematical models of a Kanban system and its modi® ed system are developed as sequential and concurrent ordering systems, respectively. By means of simulation experiments, the e ects of the autocorrelation of demand upon the performances of the systems are investigated and compared with each other. Based on the results, the procedure to design a system of production planning and inventory control is shown.

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Section: Introductionmentioning

confidence: 99%

The effect of autocorrelated demand in JIT production systems

Takahashi¹,

Nakamura²

1998

International Journal of Production Research

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“…A little introspection on the nature of burstiness in arrival processes should convince the reader of its deleterious effect on waiting times: Multiple customers arriving in a burst will obviously suffer from increased waiting times, while the lulls separating bursts waste server utilization. Indeed, various studies [5,24,29] have shown that when autocorrelated traffic is offered to a queueing system, the resulting performance measures are much worse than those corresponding to renewal traffic, differing by orders of magnitude. A growing realization of the impact of bursty traffic on queueing system performance has provided the initial motivation for devising input analysis methods that are able to capture dependence in time series; no doubt, this realization is bound to extend to other modeling domains.…”

Section: Introductionmentioning

confidence: 97%

A Survey of TES Modeling Applications

Melamed¹,

Hill²

1995

SIMULATION

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Princeton, NJ 08540 TES (Transform-Expand-Sample) is a versatile methodology for modeling general stationary time series, and particularly those that are autocorrelated. From the viewpoint of Monte Carlo simulation, TES represents a new and flexible input analysis approach. The salient feature of TES is its potential ability to simultaneously capture first-order and second-order properties of empirical time series (field measurements): Given an empirical sample, TES is designed to fit an arbitrary empirical marginal distribution (histogram) and to simultaneously approximate the leading empirical autocorrelations. Practical TES modeling is computationally intensive and can be effectively carried out only with computer support. A software modeling environment, called TEStool, has been designed and implemented to support the TES modeling methodology, through an interactive heuristic or algorithmic search approach employing extensive visualization. The purpose of this paper is to introduce TES modeling, and to offer some illustrative examples from a range of applications, including source modeling of compressed video and fault arrivals, financial modeling and texture generation. These examples demonstrate the efficacy and versatility of the TES modeling methodology, and underscore the high fidelity attainable with TES models.

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“…For example, a little introspection on the nature of burstiness in arrival processes should convince the reader of its deleterious effect on waiting times: many customers arriving in a burst will obviously suffer from increased waiting times, while the lulls separating bursts waste server utilization. Indeed, various studies (see Fendick et al 1989, Livny et al 1993, Patuwo et al 1993) have shown that when autocorrelated traffic is introduced into a queueing system, the resulting performance metrics exhibit significant degradation relative to those estimated by renewal models, often differing by orders of magnitude.…”

Section: Introductionmentioning

confidence: 98%

Applications of the TES modeling methodology

Melamed¹,

Hill²

1993

Proceedings of the 25th Conference on Winter Simulation - WSC '93

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TES (Transform-Expand-Sample)is a versatile methodology for modeling general stationary time series, and particularly those that are autocorrelated. The salient feature of TES lies in its ability to simultaneously capture firstorder and second-order properties of empirical time series ; given a sample data sequence, TES is designed to simultaneously capture any arbitrary marginal distribution and approximate the leading autocorrelations. Practical TES modeling is computationally intensive and can be effectively carried out only with software support. A computerized modeling environment, TEStool, has been designed to support the TES modeling methodology, through an interactive heuristic search approach facilitated by stateof-the-art data visualization techniques. The purpose of this paper is to present four examples of the effective use of the TES methodology to model various types of time series that arise in a variety of disciplines, ranging from manufacturing to financial modeling, with particular emphasis on video compression. These examples serve to highlight the efficacy and versatility of the TES modeling methodology.

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The Effect of Correlated Arrivals on Queues

Cited by 49 publications

References 10 publications

The effect of autocorrelated demand in JIT production systems

The effect of autocorrelated demand in JIT production systems

A Survey of TES Modeling Applications

Applications of the TES modeling methodology

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