The location-inventory-routing problem in the pallet pooling system
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
The pallet pooling system provides standard transportation packaging in a shared manner, which improves the logistics efficiency and resource utilization. It involves three key and interrelated decisions on the location of operation centers, inventory management and vehicle routing in this system, which significantly influence the overall efficiency of the system. To address this integrated location-inventory-routing problem, we develop a comprehensive mixed-integer linear programming model that incorporates the system's characteristics of multi-scale operation center location, multi-period inventory management with scheduling between operation centers, and vehicle route planning incorporating simultaneous delivery and pickup. Owing to the computational complexity, we propose a hybrid heuristic algorithm that combines genetic operators, K-Medoids clustering, and ant colony optimization to obtain high-quality solutions efficiently. Numerical experiments using benchmark datasets demonstrate both the feasibility of the developed model and the efficiency of the proposed algorithm.
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 | 0.001 | 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