An integrated stochastic EPQ model under quality and green policies: generalised cross decomposition under the separability approach
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
In this paper, a bi-objective multi-product constrained and integrated economic production quantity model is designed by considering the quality control and green production policies. The aforementioned model comes with stochastic constraints. Moreover, to create a kind of green approach policy, tax cost of greenhouse gas emissions and limitations are considered. The aim of this study is to optimise the total inventory cost and the total profit, while the stochastic constraints are satisfied. Due to the inconsistency of objectives, an Lp-metric function is utilised to integrate and achieve a single objective function. Therefore, the mathematical formulation of the problem is bi-objective stochastic mixed integer nonlinear programming large scale and hard to solve. Accordingly, generalised cross decomposition under the separability approach is utilised as an effective algorithm for global optimisation. Moreover, sensitivity analysis revealed that increasing the cost function weight versus decreasing the profit function weight leads to the change rate of the integrated-objective function becomes positive with a steep slope.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.002 | 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