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Record W3101805011 · doi:10.22215/etd/2020-14163

Equilibrium Behaviour of Double-Sided Queueing System with Dependent Matching Time

2020· dissertation· en· W3101805011 on OpenAlexaff
Cheryl Yang

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsTaxisQueueing theoryMatching (statistics)Context (archaeology)ObservableTerminal (telecommunication)PickupComputer scienceMathematical optimizationQueueOperations researchMathematicsEngineeringStatisticsTransport engineeringComputer networkPhysicsArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

In this thesis, we consider the equilibrium behaviour of a double-ended queueing system with dependent matching time in the context of taxi-passenger systems at airport terminal pickup.We extend the standard taxi-passenger model by considering random matching time between taxis and passengers in an airport terminal pickup setting.For two types of matching time distribution, we examine this model through analysis of equilibrium behaviour and optimal strategies.We demonstrate in detail how to derive the equilibrium joining strategies for passengers arriving at the terminal and the existence of a socially optimal strategies for partially observable and fully observable cases.Numerical experiments are used to examine the behaviour of social welfare and compare cases.I would like to give my deepest gratitude to my supervisor, Dr. Yiqiang Zhao, for his tremendous support throughout

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.229
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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