Centralized and hierarchical scheduling frameworks for copper smelting process
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
Optimal scheduling of copper smelting process is an ongoing challenge due to conflicting objectives of the various process units and the inter-dependencies that exist among these units. To design a scheduling framework, two potential alternatives – centralized and hierarchical approaches – can address those inter-dependencies in this process. These approaches represent the two extremes and the choice depends on the accuracy, reliability, and complexity of the scheduling task. In this study, optimization-based centralized and hierarchical scheduling frameworks are developed to find an optimal schedule for the smelting process, considering the inter-dependencies among process units. We propose a practical and effective coordination scheme for the hierarchical framework that finds a near-optimal schedule with reasonable computational demands. Two case studies are presented to demonstrate that the proposed hierarchical framework is capable of finding a near plant-wide optimum for the copper smelting process and it can be used in similar plant-wide scheduling applications.
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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 | 0.001 |
| 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