Production Policy Optimization in Flexible Manufacturing-Remanufacturing Systems
Bibliographic record
Abstract
Hybrid systems that use in their production process both raw materials (manufacturing mode), and returned products (remanufacturing mode) are considered. The system is supposed to be fully flexible and able to share its production time between manufacturing and remanufacturing. The system performance is evaluated using a piecewise linear function of serviceable and return inventories. Limited flow rate of returned products results in the state constraint on the return inventory and imposes additional limitations on the system feasibility. Such systems, to the best of the authors knowledge, were not previously considered in the literature. After characterizing manufacturing-remanufacturing strategies analytically, we propose some heuristics that approximate optimal policies in case of systems without failures, and then extend them to the case of failure-prone systems. We present the numerical study based on the solution of Hamilton-Jacobi-Bellman equations, that complements analytical results and allows to validate the proposed sub-optimal policies.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".