A two-phase multi-criteria decision support system for supply chain management
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
Multi-criteria decision-making techniques have been used to solve a range of real world problems in management science and specific supply chain management (SCM) problems (e.g. supply chain design and reconfiguration, purchasing, scheduling, supplier selection). The results obtained are encouraging. Nevertheless, robust approaches for solving multi-criteria supply chain problems are still in progress, and more research is needed before an effective and operational framework can be developed. The proposed approach introduces a two-phase hierarchical approach to solve a multi-criteria SCM problem integrating both strategic and tactical decisions where the supply chain is evaluated based on the supply chain operations reference model. The latter considers various metrics such as delivery reliability, flexibility, responsiveness and cost. The first phase evaluates different supply chains configurations using analytic hierarchy process. The second phase solves the network for the optimal safety stock placement using dynamic programming. The output from this two-phase process is a supply chain network configuration that has the right amount of safety stocks at the right place to absorb variability in demand.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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