Heterogeneous-vehicle distribution logistics planning for assembly line station materials with multiple time windows and multiple visits
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Aiming at distribution logistics planning in green manufacturing, heterogeneous-vehicle vehicle routing problems are identified for the first time with multiple time windows that meet load constraints, arrival time window constraints, material demand, etc. This problem is expressed by a mathematical model with the characteristics of the vehicle routing problem with split deliveries by order. A hybrid ant colony optimization algorithm based on tabu search is designed to solve the problem. The search time is reduced by a peripheral search strategy and an improved probability transfer rule. Parameter adaptive design is used to avoid premature convergence, and the local search is enhanced through a variety of neighborhood structures. Based on the problem that the time window cannot be violated, the time relaxation rule is designed to update the minimum wait time. The algorithm has the best performance that meets the constraints by comparing with other methods.
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