Multi-objective vessel routing problems with safety considerations: A review
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
This paper provides a review of vessel route planning with a focus on safety considerations and the complexity of multi-objective decision-making processes. This complexity arises from the difficulty of finding an appropriate balance between several objectives and safety concerns, often conflicting, that adequately reflects the preferences of the decision makers. The maritime industry faces the challenge of enhancing vessel route optimization for safety, operational efficiency, and cost-effectiveness. We thus describe quantitative methods to find routes that effectively balance multiple objectives, including safety, fuel consumption, and route duration. A significant focus is on the complexity of multi-criteria decision making in this area, highlighting various methodologies for balancing the different objectives. Safety is critical in this context, involving a thorough consideration of navigational risks, environmental factors, and compliance with International Maritime Organization regulations. Specifically, we introduce quantitative approaches for integrating key safety aspects into the decision-making process, including dynamic stability, the probability of bow slamming, and the occurrence of green water.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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