A scenario-based approach for a green aggregate production planning in a multi-site manufacturing system with workforce transferring
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents an Aggregate Production Planning (APP) model that minimizes workforce-related costs in multi-site manufacturing systems by introducing an inter-site workforce transferring policy. This novel approach reallocates workers between sites, reducing the need for hiring or layoffs. Additionally, the APP integrates environmental objectives, directly minimizing energy consumption, carbon emissions, and waste generation, forming a Green APP (GAPP). To address uncertainties in subcontractors’ costs, capacity, and overtime production, a scenario-based approach is adopted. The problem is formulated as a multi-objective scenario-based mixed-integer linear programming model and solved using a combination of the LP-metric method and fuzzy AHP. The model was validated through test problems and real-world implementation, achieving over 60% cost reduction in workforce changes. This study contributes to the APP literature by proposing inter-site workforce transfer policy, integrating environmental considerations, and addressing uncertainties in subcontractor performance.
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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