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Record W1994182583 · doi:10.1061/9780784412602.0197

Evaluating Advanced Pickup and Delivery Systems: A Simulation Study

2012· article· en· W1994182583 on OpenAlexaffabout
Liping Fu, Chaozhe Jiang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPickupParatransitComputer scienceSimulation modelingSet (abstract data type)SimulationSystems engineeringEngineeringTransport engineeringPublic transportArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a simulation model that has been developed to model a variety of technology-oriented pickup and delivery distribution systems. The paper discusses the general concepts and models applied in simulation systems, focusing on the way that various components are modeled and how they interact with each other in the overall simulation framework. The simulation system is applied to model a specialized passenger pickup and delivery system - dial-a-ride paratransit with the objective of evaluating the potential operational improvement that may be attained from the application of an automatic vehicle location system (AVL). A series of simulation experiments are performed on a set of hypothetical cases, and a realistic example was conducted from the City of Edmonton, Alberta, resulting in valuable insights into the potential impact of AVL technology.

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)0.004
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 score0.060
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.341
Teacher spread0.279 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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