A Branch-and-Price Method for a Liquefied Natural Gas Inventory Routing Problem
Why this work is in the frame
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Bibliographic record
Abstract
We consider a maritime inventory routing problem in the liquefied natural gas (LNG) business, called the LNG inventory routing problem (LNG-IRP). Here, an actor is responsible for the routing of the fleet of special purpose ships, and the inventories both at the liquefaction plants and the regasification terminals. Compared to many other maritime inventory routing problems, the LNG-IRP includes some complicating aspects such as (1) a constant rate of the cargo evaporates each day and is used as fuel during transportation; (2) variable production and consumption of LNG, and (3) a variable number of tanks unloaded at the regasification terminals. The problem is solved by a branch-and-price method. In the column generation approach, the master problem handles the inventory management and the port capacity constraints, while the subproblems generate the ship route columns. Different accelerating strategies are implemented. The proposed method is tested on instances inspired from real-world problems faced by a major energy company.
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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 | 0.001 |
| 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