Multi-period stochastic packing and shipping model for online retail
Bibliographic record
Abstract
Online retail have been continously growing in the last years. In France, during the secondquarter of 2013, online retail rose by 20% in comparison to same period of the year before.To reduce global cost, coordinating warehouse management and transport planning in a globaloptimization model was considered. In keeping with this trend, this work investigatesa new model for coordinating packaging and shipping operations. Orders are shipped using a set of delivery options, called channels. Joint Packaging and shippingenables us to define actions that influence the standard processing in term of managing peakof activity : packaging postponement, channel change. Uncertainty of orders arrival at warehouse guided us to consider stochastic optimization techniques in a rolling horizon schema. Numerical experimentation are conducted using realistic data provided by a major logistic services company.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".