A Collaborating Supply Chain Inventory Model Including Linear Time-Dependent, Inventory, and Advertisement-Dependent Demand Considering Carbon Regulations
Bibliographic record
Abstract
For carbon emission, this research study investigates a Mathematical inventory model with time, advertising, and inventory-dependent demand patterns.The main objective of this research study is to keep the total cost of retailers as well as suppliers and carbon emissions as low as possible.With collaboration and without collaboration, two cases are discussed in this proposed model.Within the first case, retailers and suppliers are not regarded as collaborators, whereas in the second case, collaboration is recognized.The optimality of the planned inventory management model is explained mathematically and theoretically in both situations.The algorithm of the mathematical solution was also properly discussed and the effects of altering various parameters are numerically studied to conduct a sensitivity analysis with the help of Mathematica software version 12.To demonstrate this model, a mathematical illustration, and a tabular and graphical representation, have been also provided.Ultimately, this model reaches a flourishing managerial suggestion and conclusion.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".