Optimal server allocation in general, finite, multi‐server queueing networks

Smith, J. MacGregor; Cruz, Frederico R. B.; Woensel, Tom Van

doi:10.1002/asmb.813

Cited by 16 publications

(8 citation statements)

References 34 publications

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“…The objective function is then CAP = min ∑ ∈ . The CAP was considered by Smith et al [42] in which a methodology was developed built upon two-moment approximations to the service time distribution embedded in the GEM for computing the performance measures in complex finite queueing networks and Powell's [39] algorithm for optimally allocating servers to the network topology.…”

Section: Optimization Modelsmentioning

confidence: 99%

Finite Queueing Modeling and Optimization: A Selected Review

Cruz

Woensel

2014

Journal of Applied Mathematics

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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).

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Section: Optimization Modelsmentioning

confidence: 99%

Finite Queueing Modeling and Optimization: A Selected Review

Cruz

Woensel

2014

Journal of Applied Mathematics

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“…The BCAP is formulated as a single‐objective optimization problem (Smith et al, 2009). In our formulation, we assume that decision makers want to minimize their investment in buffers and servers, but want to assure a certain minimum service level for their customers.…”

Section: Model Formulation and Implicationsmentioning

confidence: 99%

“…There is a vast amount of literature on the optimal allocation of servers . Many studies have been done considering single nodes, open and closed networks, infinite and finite buffer waiting room, and exponential service systems (Smith et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Buffer and server allocation in general multi‐server queueing networks

Woensel¹,

Andriansyah²,

Cruz³

et al. 2010

Int Trans Operational Res

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This paper deals with the joint optimization of the number of buffers and servers, an important issue since buffers and servers represent a significant amount of investment for many companies. The joint buffer and server optimization problem (BCAP) is a non-linear optimization problem with integer decision variables. The performance of the BCAP is evaluated by a combination of a two-moment approximation (developed for the performance analysis of finite general-service queues) and the generalized expansion method (a wellknown method for performance analysis of acyclic networks of finite queues). A standard non-linear optimization package is used to optimize the BCAP for a large number of experiments. A comprehensive set of numerical results is presented. The results show that the methodology is capable of handling the trade-off between the number of servers and buffers, yielding better throughputs than previously published studies. Also, the importance of the squared coefficient of variation of the service time is stressed, since it strongly influences the approximate optimal allocation.

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“…Both BAP and CAP are probably among the most well-known optimal resource allocation problems [16] . For instance, Cruz et al [17] and Smith et al [18] looked into the BAP, both in a single and in a multi-server setting, and Smith et al [19] proposed algorithms to solve the CAP. However, the routing probabilities are usually assumed to be known beforehand for BAP and CAP [20] .…”

Section: Introductionmentioning

confidence: 99%

Optimal Routing in General Finite Multi-Server Queueing Networks

Woensel

Cruz

2014

PLoS ONE

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The design of general finite multi-server queueing networks is a challenging problem that arises in many real-life situations, including computer networks, manufacturing systems, and telecommunication networks. In this paper, we examine the optimal routing problem in arbitrary configured acyclic queueing networks. The performance of the finite queueing network is evaluated with a known approximate performance evaluation method and the optimization is done by means of a heuristics based on the Powell algorithm. The proposed methodology is then applied to determine the optimal routing probability vector that maximizes the throughput of the queueing network. We show numerical results for some networks to quantify the quality of the routing vector approximations obtained.

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Optimal server allocation in general, finite, multi‐server queueing networks

Cited by 16 publications

References 34 publications

Finite Queueing Modeling and Optimization: A Selected Review

Finite Queueing Modeling and Optimization: A Selected Review

Buffer and server allocation in general multi‐server queueing networks

Optimal Routing in General Finite Multi-Server Queueing Networks

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