MétaCan
Menu
Back to cohort
Record W3161442960 · doi:10.5585/exactaep.2021.11398

A decomposition resolution approach for a production-inventory-distribution-routing problem

2021· article· pt· W3161442960 on OpenAlex
William de Paula Ferreira, Leonardo Carlos Da Cruz, Michael David de Souza Dutra

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

VenueExacta · 2021
Typearticle
Languagept
FieldDecision Sciences
TopicOperations Management Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

O objetivo deste estudo é desenvolver uma solução para o problema de distribuição proposto pelos jogos matemáticos de 2017-2018, organizado conjuntamente pela Federação Francesa de Jogos Matemáticos e Empresa de Modelagem Matemática. Conhecido na literatura como um problema de produção-estoque-distribuição-roteamento (PIDRP), este é um problema de otimização combinatória NP-difícil, ainda pouco explorado na literatura. Esta pesquisa é baseada em modelos quantitativos e combina métodos exatos e heurísticos para propor uma abordagem de resolução de múltiplas fases para o PIDRP. Os resultados mostram que o uso de clusters respeita aspectos operacionais práticos e oferece boas soluções para o PIDRP no planejamento de curto e longo prazo. A contribuição teórica deste estudo está na estratégia de modelagem do PIDRP, e a contribuição prática consiste na solução de um PIDRP real baseado em técnicas de otimização.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.082
GPT teacher head0.372
Teacher spread0.290 · 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