A two-stage stochastic programming method for designing multi-stage global supply chains with stochastic demand
Why this work is in the frame
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Bibliographic record
Abstract
This paper encompasses the design of a multi-stage global supply chain with stochastic demand. The network consists of manufacturing sites, distribution centres and retail zones situated at both domestic and international locations. Tactical level decisions to be made are the selection of international outsourcing partners, transportation modes and the capacity of each facility. To provide a practical decision support tool for the design of global supply chains, we consider the existence of exchange rate variations and the presence of economies of scale in production which lead to different capacity expansion and outsourcing policies. We formulate the problem as a mixed-integer programming (MIP) model with the objective of minimising the overall costs and maximising the expected average service level. A two-stage stochastic programming method is used to handle the stochasticity in demand. Finally, the proposed model is applied to various cases to demonstrate its applicability in facilitating decision making for managers.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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