The Pickup And Delivery Problem With Time Windows And Transshipment
Why this work is in the frame
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Bibliographic record
Abstract
Pickup and delivery problems with time windows are frequently encounlcred by courier companies. These companies serve customers that require transporiation of a package from a pickup location to a delivery location. This paper presents an empirical study on usefulness of transshipment points in such a conlexl. Transshipnicnl allows for a request to be served by Iwo vehicles: one vehicle collects the load at the pickup location, drops it al a transshipment point, and another vehicle carries the load lo the delivery location. The motivation for this work came from the practice observed in a large San Francisco based courier company that allows transshipment of loads between vehicles. The company serves large geographic area covering several neighboring cities. The main reasoning behind allowing transshipment lies in the idea of keeping drivers in their home area. We have investigated a generalization of ihis transshipment practice, allowing vehicles to move through entire service area in order to evaluate the usefulness of transshipment. We identify circumstances under which transshipment may be beneficial.
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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 | 0.001 | 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 | 0.001 |
| 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