Optimal Method for Allocation of Tractors and Trailers in Daily Dispatches of Road Drops and Pull Transport
Why this work is in the frame
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Bibliographic record
Abstract
The domestic road drop and pull transportation system allows only tractors and semitrailers. In this mode, any tractors can only run with one semitrailer at a time or with no load. By optimizing the tractor scheduling plan, the no-load mileage of the tractor can be reduced, which can improve the efficiency and reduce the number of tractors. In this article, we have developed an optimization model for the tractor routing scheme to minimize the total cost of the drop and pull transportation system, which can limit the total number of tractors because the tractor can transport as many semitrailers to the destination as possible within the time window. Focusing on this mixed integer nonlinear problem, an improved ant search algorithm is designed. Finally, with Sichuan’s Anji Logistics Enterprise as the background, this tractor scheduling optimization model is applied to an ideal network and a real scenario. The results show that the optimized system reduces total cost by approximately18.7% and the ratio of tractors to semitrailers is approximately 1 : 3.31.
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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 | 0.000 |
| 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