A bi-objective location routing optimization with fuzzy time-dependent societal risks for enhancing urban medical waste management system
Why this work is in the frame
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Bibliographic record
Abstract
This paper aims to enhance medical waste management by adding new recycling centers or upgrading existing facilities, properly planning vehicle acquisition and routing under the consideration of both societal and economic impacts. Specifically, we focus on the threats posed to the surrounding population during collection and recycling by formulating a fuzzy time-dependent societal risk assessment that integrates the exposure distance estimated in terms of fuzzy vehicle speed into the traditional risk model. Then, considering multiple types of medical wastes and compatible vehicles, a bi-objective location-routing model is developed to make location-routing decisions simultaneously minimizing societal risk and system cost. The complexity of the resulting mathematical model motivates the adoption of three multi-objective optimization approaches, which are used to test our proposed model using a real-life network in Shenzhen, China. This research suggests an affordable opportunity to upgrade the current waste management system to align with the post-pandemic “new normal” by adapting existing facilities for medical waste recycling. The proposed risk measure results in better-controlled total and transportation risks, as well as a more equitable distribution of risk. Compared to the current policy, our recommended plan can reduce the system risk by more than 50% with only a 22% increase in cost.
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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 | 0.000 |
| 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 it