Development of a Fuzzy-Queue-Based Interval Linear Programming Model for Municipal Solid Waste Management
Why this work is in the frame
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Bibliographic record
Abstract
In this study, a fuzzy-queue-based interval linear programming (FQ-ILP) model was first developed through introducing FQ model into an ILP framework. The FQ-ILP model can not only address system uncertainties with complex presentations, but also reflect the influence of FQ in decision-making problems. Moreover, it can be used for analyzing various policy scenarios that are associated with different waiting costs, fuzzy waiting times, and different operation costs. The method has been applied to a typical case study area for long-term municipal solid waste management planning. Interval solutions associated with fuzzy arrival rate, fuzzy service rate, and different waiting costs have been generated. They can be further used for generating decision alternatives and thus help waste managers to identify desired policies under various environmental, economic, and fuzzy queuing problems. Compared with the conventional optimization methods, the developed FQ-ILP model can more actually reflect the complexity of municipal solid waste management systems and provide more useful information for decision makers under uncertainty, resulting in increased system robustness. Results also suggest that the proposed method is applicable to other environment problems that involve uncertainties presented in multiple formats in the queuing models.
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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) | 0.000 | 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