A Heuristic for the Time-Dependent Vehicle Routing Problem with Time Windows
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We consider the Time-Dependent Vehicle Routing Problem (tdvrptw), a generalization of the Vehicle Routing Problem with Time Windows (vrptw) where the travel time between any pair of clients can vary over the time. Its purpose is to better handle the dynamic nature of the travel time, especially in urban areas where traffic congestion can have a significant impact on the transportation. We propose a heuristic based on column generation and on Variable Neighborhood Descent (vnd) for solving the tdvrptw. Several neighborhoods are used to identify improving columns at each iteration of the column generation process. Those columns are then stored in a shared pool. In the same time, the integer master problem is solved and its solution is then improved by the vnd. Both total distance and number of vehicle criteria are considered. Numerical results are then presented to show the interest of our approach.
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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 | 0.005 | 0.001 |
| 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 | 0.001 | 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