Round-Trip Emergency Supply Distribution Model Based on Nonfixed Routes
Bibliographic record
Abstract
In the face of increasing natural or man-made disasters, rapid and effective emergency dispatch and organization are of great significance to ensure the life safety of people and reduce social losses. In view of the long duration, strong demand urgency, and relatively limited transportation capacity after catastrophic events, this paper proposes a round-trip emergency supply distribution model based on nonfixed routes. This model includes two main features: (1) round trip: emergency vehicles can travel back and forth to distribute supplies; (2) unfixed routes: distribution routes of the same emergency vehicle could be variable in different trips. In order to ensure the timeliness and fairness of the supply distribution scheme, the model objective function is set to minimize the total supplies’ waiting time at all demand points. According to model features, 4 constraints are set, including flow balance, capacity, vehicle scheduling, and time window. On this basis, a compound algorithm combining 2-opt and tabu search is designed to obtain the optimal plan of the model. To verify the effectiveness and superiority of the model and solution method, a case study based on the Sioux Falls network is carried out. Compared with the traditional method, the objective function is optimized by 11.92%. In fact, under the control of multiple constraint conditions, the model well fits the actual application scenarios, which can provide theoretical guidance and decision support for the distribution of relevant emergency supplies.
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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 | 0.000 | 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 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".