CROSS‐DOCKING AND ITS IMPLICATIONS IN LOCATION‐DISTRIBUTION SYSTEMS
Why this work is in the frame
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Bibliographic record
Abstract
Cross‐docking replaces traditional warehousing, enabling continuous flow of items without storage. Here we model location‐distribution networks, that include cross‐docking facilities, to obtain the latter's impact on the supply chain. We formulate optimization models to minimize total cost in three multi‐echelon networks, each model generalizing the preceding one. The first includes a single manufacturer, one product type, and multiple customers. Cross‐docks are to be located between origin and destinations. Besides solving optimally, a tool for quantitative analysis of direct‐shipment decisions is developed. The second model considers more than one product: We determine a cost‐effective sequence of items for indirect shipment (via cross‐docks). Finally, in a network with multiple origins, optimal solutions are obtained for 40 medium‐sized and larger examples.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it