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Record W2136642745 · doi:10.1287/trsc.1050.0139

Dispatching Buses in a Depot Using Block Patterns

2006· article· en· W2136642745 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTransportation Science · 2006
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsUniversité du Québec à MontréalPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDepotTransport engineeringBlock (permutation group theory)Computer scienceOperations researchEngineeringGeographyMathematics

Abstract

fetched live from OpenAlex

In this article we consider the problem of assigning parking slots to buses of different types so that the required buses can be dispatched easily in the morning. More precisely, if a bus of a certain type is needed at a given time, the buses that precede it in the lane must have departed already. Thus care must be taken to ensure that the buses arriving in the evening are parked in an order compatible with the types required for the morning departures. Maneuvers (i.e., rearrangements of buses within lanes) might be necessary to achieve this goal. Because the transit authorities need robust solutions to this problem (known as the dispatching problem in the literature), we formulate a model in which the depot lanes are filled according to specific patterns, called one-block or two-block patterns. We present two versions of this model, study their properties, and show that some real-life instances can be solved within reasonable times by a commercial MIP solver. We also demonstrate that the solutions of the model are very robust, and can thus be used by transit authorities.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.283
Teacher spread0.260 · 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