Vessel Service Planning in Seaports
Bibliographic record
Abstract
An Integrated Approach to Managing Vessel Service in Seaports Efficient vessel service is of utmost importance in the maritime supply chain. When serving a group of incoming vessels, berth allocation and pilotage planning are the two most important decisions made by a seaport. Although they are closely correlated, the berth allocation problem and pilotage planning problem are often solved sequentially, leading to suboptimal or even infeasible solutions for vessel services. In “Vessel Service Planning in Seaports,” Wu, Adulyasak, Cordeau, and Wang focus on a vessel service planning problem that optimizes berth allocation and pilotage planning in combination. To solve the joint problem, the authors develop an exact solution method that combines Benders decomposition and column generation within an efficient branch-and-bound framework. They also propose acceleration strategies that significantly improve the performance of the algorithm. Test instances from one of the world's largest seaports are used to validate the effectiveness of the approach and demonstrate the value of integrated planning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".