Loading and scheduling outbound trucks at a dispatch warehouse
Why this work is in the frame
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Bibliographic record
Abstract
We address the operational planning problem of loading and scheduling outbound trucks at a dispatch warehouse shipping goods to several customers. This entails, first, assigning shipments to outbound trucks given the trailers’ capacities and, second, scheduling the trucks’ processing at the dock doors such that the amount of required resources at the terminal (e.g., dock doors and logistics workers) does not exceed the available levels. The trucks should be scheduled as late as possible within their time windows, but no later than the deadlines of the loaded shipments. Such planning problems arise, e.g., at dispatch warehouses of automotive parts manufacturers supplying parts to original equipment manufacturers in a just-in-time or even just-in-sequence manner. We formalize this operational problem and provide a time-indexed mixed-integer linear programming model. Moreover, we develop an exact branch-and-price algorithm, which is shown to perform very well, solving most realistically sized problem instances to optimality within a few minutes. In a numerical study, we also look into the interplay between the time window policy for trucks and just-in-time deliveries. Finally, we find evidence that too small a workforce or too few outbound dock doors in the dispatch warehouse can substantially compromise the punctuality of the deliveries.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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