Sustainable risk mitigation in hazardous material transportation
Bibliographic record
Abstract
The transportation of hazardous material involves the movement of freight representing a high risk to health, safety, and the environment. Due to its nature, hazardous material transportation is regulated by strict laws and must be treated separately from classical transportation. This study addresses road transportation of hazardous materials as a variant of the hazmat vehicle routing and scheduling problem with time windows. The model incorporates a multi-criteria risk measure, balancing factors such as accident probability, population density, distance from fire stations, and traffic conditions, while considering time-dependent travel times divided into distinct time zones. The problem is formulated as a three-objective optimization model to minimize total risk, arrival time, and vehicle cost. A late acceptance hill-climbing heuristic is introduced to obtain feasible solutions. Computational experiments on test instances demonstrate the heuristic’s efficiency and its ability to generate high-quality solutions in reduced execution times. Subsequently, the heuristic is applied to a case study on a Northern Italy road network involving the transportation of compressed oxygen by a logistics operator, providing actionable managerial insights.
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.
How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".