A consignment stock policy for a two-level supply chain with imperfect quality items
Bibliographic record
Abstract
A consignment stock is a type of supply-chain coordination for the management of supply-chains in which there is a joint vendor and buyer policy that is mainly focused on having the vendor manage the buyer's inventory. This thesis aims to investigate the consignment stock strategy in a single-vendor single-buyer supply-chain context considering imperfect items that may be produced from an imperfect production process. It develops a flexible mathematical model that allows for managerial decisions with regards to imperfect items and seeks to minimize costs (maximize profits) of the supply-chain. Such managerial decisions include scrapping items at a cost, selling them for a marginal profit to a secondary market, applying re-work, and/or applying minor setups to restore the production process. Results show that the introduction of imperfect items increases the batch size and reduces the number of shipments. Minor setups were shown to reduce cost, increase the number of shipments and reduce its size.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".