Integrated design of emergency shelter and medical networks considering diurnal population shifts in urban areas
Why this work is in the frame
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Bibliographic record
Abstract
This article addresses an emergency shelter and medical network design problem by integrating evacuation and medical service activities and considering diurnal population shifts to respond to large-scale natural disasters in urban areas. A multi-objective mixed-integer programming model that incorporates the characteristics of diurnal population shifts is developed to determine the configuration of the integrated emergency shelter and medical network. An accelerated Benders decomposition algorithm is then devised to solve large-scale problems in reasonable time. A realistic case study on the Xuhui District of Shanghai City in China and extensive numerical experiments are presented to demonstrate the effectiveness of the proposed model and solution method. Computational results suggest that more emergency shelters and emergency medical centers should be established when accounting for diurnal population shifts than when diurnal population shifts are not considered. The accelerated Benders decomposition algorithm is significantly more time efficient as compared with the CPLEX solver.
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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 | 0.000 | 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) | 0.004 | 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