Finite Queueing Modeling and Optimization: A Selected Review

F R B Cruz,T Van Woensel

doi:10.1155/2014/374962

F R B Cruz, T Van Woensel

Open Access

https://doi.org/10.1155/2014/374962

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Abstract

This review provides an overview of the queueing modeling issues and the related performance evaluation and optimization approaches framed in a joined manufacturing and product engineering. Such networks are represented as queueing networks. The performance of the queueing networks is evaluated using an advanced queueing network analyzer: the generalized expansion method. Secondly, different model approaches are described and optimized with regard to the key parameters in the network (e.g., buffer and server sizes, service rates, and so on).

Highlights

Queueing theory is the mathematical study of waiting lines and it enables the mathematical analysis of several related processes, including arrivals at the queue, waiting in the queue, and being served by the server
The focus in this paper is on finite buffer queueing networks which are characterized by the blocking effect, which eventually degrades the performance, commonly measured via, for example, the throughput of the network
This review aims at providing an overview of modeling, performance evaluation, and optimization approaches from a queueing theory point of view

Summary

Introduction

Queueing theory is the mathematical study of waiting lines and it enables the mathematical analysis of several related processes, including arrivals at the queue, waiting in the queue, and being served by the server. The theory enables the derivation and calculation of several performance measures which can be used to evaluate the performance of the queueing system under study. The focus in this paper is on finite buffer queueing networks which are characterized by the blocking effect, which eventually degrades the performance, commonly measured via, for example, the throughput of the network. Queueing modeling and optimization of large scale manufacturing systems and complex production lines have been and continue to be the focus of numerous studies for decades (e.g., see Smith [1,2,3]). Queueing networks are commonly used to model such complex systems (see Suri [4]). There are other methodologies tailored for different settings as, for instance, simulation methods (see Law and Kelton [5]) and advanced methods that explore the spectral characteristics of the associated matrices in Markovian models (e.g., see the works of Yeralan and Tan [6] and Fadiloglu and Yeralan [7], among others)

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