AMVA based solution procedures for open queueing networks with a population constraint

Ronald Buitenhek; Geert-Jan van Houtum; Willem H.M. Zijm

doi:10.1023/A:1018967622069

AMVA based solution procedures for open queueing networks with a population constraint

Ronald Buitenhek
, Geert-Jan van Houtum
, Willem H.M. Zijm

Stochastic Operations Research

Research output: Contribution to journal › Article › Academic › peer-review

51 Citations (Scopus)

14 Downloads (Pure)

Abstract

We propose a new method for the performance evaluation of Open Queueing Networks with a Population Constraint (represented by a set of tokens). The method is based on the application of Approximate Mean Value Analysis (AMVA) algorithms. We present procedures for single class networks and for multiple class networks, subject to either a common constraint (shared tokens) or to class‐based constraints (dedicated tokens). In fact, the new method is a unified framework into which all procedures for the different types of networks fit. We show how the new method relates to well‐known methods and present some numerical results to indicate its accuracy.

Original language	English
Pages (from-to)	15-40
Number of pages	25
Journal	Annals of operations research
Volume	93
DOIs	https://doi.org/10.1023/A:1018967622069
Publication status	Published - 2000
Event	International Workshop on Performance Evaluation and Optimization of Production Lines 1997 - Samos Island, Greece Duration: 19 May 1997 → 22 May 1997

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abstract = "We propose a new method for the performance evaluation of Open Queueing Networks with a Population Constraint (represented by a set of tokens). The method is based on the application of Approximate Mean Value Analysis (AMVA) algorithms. We present procedures for single class networks and for multiple class networks, subject to either a common constraint (shared tokens) or to class‐based constraints (dedicated tokens). In fact, the new method is a unified framework into which all procedures for the different types of networks fit. We show how the new method relates to well‐known methods and present some numerical results to indicate its accuracy.",

author = "Ronald Buitenhek and \{van Houtum\}, Geert-Jan and Zijm, \{Willem H.M.\}",

year = "2000",

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language = "English",

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AU - Buitenhek, Ronald

AU - van Houtum, Geert-Jan

AU - Zijm, Willem H.M.

PY - 2000

Y1 - 2000

N2 - We propose a new method for the performance evaluation of Open Queueing Networks with a Population Constraint (represented by a set of tokens). The method is based on the application of Approximate Mean Value Analysis (AMVA) algorithms. We present procedures for single class networks and for multiple class networks, subject to either a common constraint (shared tokens) or to class‐based constraints (dedicated tokens). In fact, the new method is a unified framework into which all procedures for the different types of networks fit. We show how the new method relates to well‐known methods and present some numerical results to indicate its accuracy.

AB - We propose a new method for the performance evaluation of Open Queueing Networks with a Population Constraint (represented by a set of tokens). The method is based on the application of Approximate Mean Value Analysis (AMVA) algorithms. We present procedures for single class networks and for multiple class networks, subject to either a common constraint (shared tokens) or to class‐based constraints (dedicated tokens). In fact, the new method is a unified framework into which all procedures for the different types of networks fit. We show how the new method relates to well‐known methods and present some numerical results to indicate its accuracy.

U2 - 10.1023/A:1018967622069

DO - 10.1023/A:1018967622069

M3 - Article

SN - 0254-5330

VL - 93

SP - 15

EP - 40

JO - Annals of operations research

JF - Annals of operations research

T2 - International Workshop on Performance Evaluation and Optimization of Production Lines 1997

Y2 - 19 May 1997 through 22 May 1997

ER -

AMVA based solution procedures for open queueing networks with a population constraint

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