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Un Modèle Pour La Conception D’Un Réseau De Distribution Avec Localisation, Aefectation Et Stocks

2006· article· fr· W2401579653 on OpenAlexaffvenue
Guillaume Hamer-Lavoie, Jean‐François Cordeau

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2006
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Cel article présente un modèle de programmalion linéaire en variables mixtes pour un problème de conception d’un réseau de distribution dans lequel on doit à la fois localiser des entrepôts, atfecter les clients à ces entrepôts, déterminer les niveaux de stocks à maintenir pour répondre a la demande stochastique des clients et choisir les modes de transport a iitiiiser pour le reapprovisionnement. Le problème esl défini sur un horizon de plusieurs périodes au cours desquelles la distribution de la demande peut varier. Afin d’accélérer la résolution du problème par une mèthode de séparation et évaluation, plusieurs inégalités valides sont présentées. Les résultats d’expériences de calcul sont rapportés pour des instances comportant jusqu’à 48 clients. 16 produits et 12 périodes.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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

Citations5
Published2006
Admission routes2
Has abstractyes

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