Branch-and-Price-and-Cut for the Split-Delivery Vehicle Routing Problem with Time Windows
Why this work is in the frame
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Bibliographic record
Abstract
This paper addresses the split-delivery vehicle routing problem with time windows (SDVRPTW) that consists of determining least-cost vehicle routes to service a set of customer demands while respecting vehicle capacity and customer time windows. The demand of each customer can be fulfilled by several vehicles. For solving this problem, we propose a new exact branch-and-price-and-cut method, where the column generation subproblem is a resource-constrained elementary shortest-path problem combined with the linear relaxation of a bounded knapsack problem. Each generated column is associated with a feasible route and a compatible delivery pattern. As opposed to existing branch-and-price methods for the SDVRPTW or its variant without time windows, integrality requirements in the integer master problem are not imposed on the variables generated dynamically, but rather on additional variables. An ad hoc label-setting algorithm is developed for solving the subproblem. Computational results show the effectiveness of the proposed method.
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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 | 0.002 | 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 | 0.001 | 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