Capacitated Multiechelon Inventory Systems: Policies and Bounds
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
We study a periodically reviewed multiechelon serial inventory system with a capacity constraint on the order quantity at each stage. The cost criterion we use to evaluate inventory policies for this system is the sum of the expected long-run average holding and shortage costs. It is well known that for this problem, characterizing the structure of the optimal policy and computing it are very difficult. We consider the use of echelon base-stock policies for our system (even though they are known to be suboptimal) and propose algorithms for finding base-stock levels that are easy to understand and implement. We derive bounds on the ratios between the costs achieved by our algorithms and the optimal costs (over all policies). For light-tailed demand distributions, our algorithms are shown to be asymptotically optimal in the sense that our bounds are close to one in high service-level environments. Our computational investigations reveal that our algorithms perform well even under modest service levels.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it