Scenario-based designing of closed-loop supply chain with uncertainty in returned products
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
Closed-loop supply chain management is an effective and efficient solution for a set of activities to retrieve a product from a customer and improve its value or to dispose it. Today, designing and planning a closed-loop chain is an inevitable but difficult task. In this research, a scenariobased modeling approach is presented by considering both forward and reverse flows as a closedloop supply chains in steel industry. The proposed study also develops a multi-product and multiperiod model based on a mixed integer linear programming (MILP) approach for profit maximization. The study also considers uncertainty in the amount of raw material, processing, storage and distribution of several products flow. Uncertainty is associated with the quantity and quality of the products in the reverse flow, which are directly affected by customers and sorting centers, respectively. Finally, the model is deployed in Steel industry with real data. The results show that by increasing the quality level of returned products the need for raw materials is reduced and the total profit of the supply chain is increased.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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