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Record W2614002522

Benders Decomposition for Production Routing under Demand Uncertainty

2012· article· fr· W2614002522 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

VenueLes Cahiers du GERAD · 2012
Typearticle
Languagefr
FieldEngineering
TopicReliability and Maintenance Optimization
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMathematical optimizationProduction (economics)GeneralizationRouting (electronic design automation)Pareto principleUpper and lower boundsProduct (mathematics)Time horizonBranch and boundDecompositionBranch and cutComputer scienceMathematicsOperations researchLinear programmingEconomics
DOInot available

Abstract

fetched live from OpenAlex

The production routing problem (PRP) is a generalization of the inventory routing problem and concerns the production and distribution of a single product from a production plant to multiple customers using capacitated vehicles in a discrete- and finite-time horizon. In this study, we consider the stochastic PRP with demand uncertainty in two-stage and multistage decision processes. The decisions in the first stage include production setups and customer visit schedules, while the production and delivery quantities are determined in the subsequent stages. We introduce formulations for the two problems, which can be solved by a branch-and-cut algorithm. To handle a large number of scenarios, we propose a Benders decomposition approach, which is implemented in a single branch-and-bound tree and enhanced through lower-bound lifting inequalities, scenario group cuts, and Pareto-optimal cuts. For the multistage problem, we also use a warm start procedure that relies on the solution of the simpler two-stage prob...

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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