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Record W1989850675 · doi:10.1002/net.3

The capacitated arc routing problem with intermediate facilities

2001· article· en· W1989850675 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.

Bibliographic record

VenueNetworks · 2001
Typearticle
Languageen
FieldEngineering
TopicVehicle Routing Optimization Methods
Canadian institutionsHEC MontréalUniversité de Montréal
Fundersnot available
KeywordsArc routingBenchmark (surveying)Arc (geometry)Mathematical optimizationRouting (electronic design automation)Computer scienceRelaxation (psychology)Set (abstract data type)Integer programmingInteger (computer science)Upper and lower boundsMathematicsComputer networkGeography

Abstract

fetched live from OpenAlex

Abstract This article introduces the Capacitated Arc Routing with Intermediate Facilities (CARPIF), a variant of the classical Capacitated Arc Routing Problem (CARP) in which the vehicle may unload or replenish at intermediate facilities. Two lower bounds are developed for the CARPIF: The first is based on the Rural Postman Problem (RPP) and the second one uses a relaxation of an integer linear formulation of the problem. Two upper bounds are also developed, based on the solution of an RPP and of a CARP. Computational results on a set of benchmark instances confirm the quality of the proposed bounds. © 2001 John Wiley & Sons, Inc.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.216
Teacher spread0.204 · 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