A genetic-algorithm-aided fuzzy chance-constrained programming model for municipal solid waste management
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
A genetic-algorithm-aided fuzzy chance-constrained programming (GAFCCP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. The proposed model is an innovative combination of the genetic algorithm (GA) and fuzzy chance-constrained programming (FCCP) method and thus makes a unique contribution to enhancing the feasibility and applicability of the optimization model. The GA was capable of tackling the complicated fuzzy membership function and was used to seek optimal solutions by progressively evaluating the performance of the individual solutions; meanwhile, FCCP ensured that the fuzzy constraints were satisfied at specified confidence levels, leading to cost-effective solutions under acceptable risk magnitudes. A long-term regional waste management model of Zhongshan City, China, was formulated to demonstrate the applicability of the proposed GAFCCP model. The comparison results with ongoing treatment schemes demonstrated the superiority of the generated model solutions in the aspects of cost reduction and greenhouse gas emission mitigation.
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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