A Meta-Heuristic Solution Approach to Isolated Evacuation Problems
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 an approximation method for the optimization of isolated evacuation operations, modeled through the recently introduced Isolated Community Evacuation Problem (ICEP). This routing model optimizes the planning for evacuations of isolated areas, such as islands, mountain valleys, or locations cut off through hostile military action or other hazards that are not accessible by road and require evacuation by a coordinated set of special equipment. Due to its routing structure, the ICEP is NP-complete and does not scale well. The urgent need for decisions during emergencies requires evacuation models to be solved quickly. Therefore, this paper investigates solving this problem using a Biased Random-Key Genetic Algorithm. The paper presents a new decoder specific to the ICEP, that allows to translate in between an instance of the S-ICEP and the BRKGA. This method approximates the global optimum and is suitable for parallel processing. The method is validated through computational experiments.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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