Reflections on queue modelling from the last 50 years

Worthington, David

doi:10.1057/jors.2008.178

Cited by 41 publications

(21 citation statements)

References 69 publications

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“…Another problem with logistics studies (more specifically the operations research literature) is that while the prescribed models are powerful, they are often impractical for logistics managers to apply due to their complexity [36][37][38][39][40][41]. USA-based university MIT Professor John Little (well known for Little's Law [42]) complained: ''managers don't understand the models'' [40].…”

Section: Methods and Case Studymentioning

confidence: 99%

Applying multidisciplinary logistic techniques to improve operations productivity at a mine

Strang

2011

Logist. Res.

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This case study uses a surface mine to investigate multidisciplinary logistics analysis methods for improving refinery operations. Existing resource scheduling, inventory forecasting, and economic production quantity procedures have not been able to identify how to improve productivity. The objective was to locate and demonstrate proven techniques from operations research (and other related disciplines) which could be applied to solve logistics problems. Historical operations data along with a new sample (n = 140) were utilized for the analysis. Preliminary parametric tests failed, but later a multiple server queue model was developed by integrating nonparametric techniques, waiting line theory, stochastic probabilities, and break-even scenario analysis. Quantitative and qualitative data were analyzed, resulting in a solution to increase truck arrival rates by 10% which was projected to increase refinery utilization by 7-77%, thereby generating a potential productivity savings of $161,223.31 per year.

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Section: Methods and Case Studymentioning

confidence: 99%

Applying multidisciplinary logistic techniques to improve operations productivity at a mine

Strang

2011

Logist. Res.

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“…numerical methods and simulation methods (which are, in fact, statistical methods). These three approaches are recognized in the referential literature (Nikolić, 2008), (Worthington, 2009).…”

Section: Military Queueing Systemsmentioning

confidence: 99%

The 110th anniversary of queueing theory: Its applications in the military

Nikolic¹

2019

Vojnotehnički glasnik

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The aim of the paper is to present selected examples of queueing theory applications to problems in the military and defence domain, to mark the 110 th anniversary of queueing theory. The intention was to find and present more works from domestic authors published in a longer period in order to promote the theory in the domestic military and defence circles thus motivating future research related to waiting lines phenomena. In dealing with military queueing phenomena, researchers are usually faced with some specific requirements which involve a multidisciplinary approach. In the queueing theory community, it is recognized that solutions to queueing problems could be reached in three ways: by analytical, numerical and simulation methods. Not all queueing problems are solvable by analytics or by numerical mathematics and, for such problems in particular, simulation methodology is a resolving tool.

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“…It attempts to ingest the difficulties and impact of constraints that favour the mathematical model in numerical analysis rather than reality [33]. This study implements an analytical model using SimEvents a discrete time event tool to examine the performance of queuing system [34]. SimEvents is a MATLAB time or event based toolbox which provides discrete-event simulation engine and component library containing predefined blocks with different system functionalities such as entity generators, FIFO and Priority queue rules, Signal Scope, path combiner, set attribute, etc.…”

Section: Simulation Model (Sm) Using Simevents Toolboxmentioning

confidence: 99%

“…3b. The simulation model considered arrivals at discrete inter-arrival time with unsteady arrivals at the initial stage [21], [34], which leads to time lost or gain in the process before stability was installed as shown in Fig. 4a.…”

Section: Average Queue Lengthmentioning

confidence: 99%

Modelling of queuing process at airport check-in system: a case study of Manchester and Leeds-Bradford airports

Adeke

2018

Nig. J. Tech.

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This study built a Simulation Model (SM) using SimEvents toolbox in MATLAB for implementing Analytical Models (AM) of queuing process at airport check-in system. Air travel demand data for Manchester and Leeds-Bradford airports in 2014 were adopted for validation of the model. There was no statistical difference between utilisation factor (UF) and service times of AM and SM outputs. Differences in AM and SM outputs for average queue length, average waiting time on queue and average number of arrivals and throughputs were attributed to variations in discrete time events considered by SM in contrary to the AM which assumed constant values for the process. The SM exhibited stochastic behaviour which actually depicts reality hence produces more reliable results. Stochastic analysis methods are therefore recommended for queuing analysis to achieve accurate results. The SM is therefore recommended to give Airport managers prior knowledge of system performance for planning and improved level of service (LOS) at airports.

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Reflections on queue modelling from the last 50 years

Cited by 41 publications

References 69 publications

Applying multidisciplinary logistic techniques to improve operations productivity at a mine

Applying multidisciplinary logistic techniques to improve operations productivity at a mine

The 110th anniversary of queueing theory: Its applications in the military

Modelling of queuing process at airport check-in system: a case study of Manchester and Leeds-Bradford airports

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