The Stochastic Multiperiod Location Transportation Problem
Why this work is in the frame
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Bibliographic record
Abstract
This paper studies a stochastic multiperiod location-transportation problem (SMLTP) characterized by multiple transportation options, multiple demand periods, and a stochastic demand. We consider the determination of the number and location of the depots required to satisfy customer demand as well as the mission of these depots in terms of the subset of customers they must supply. The problem is formulated as a stochastic program with recourse, and a hierarchical heuristic solution approach is proposed. It incorporates a tabu search procedure, an approximate route length formula, and a modified procedure of Clarke and Wright (Clarke, G., J. W. Wright. 1964. Scheduling of vehicles from a central depot to a number of delivery points. Oper. Res. 12 568–581). Three neighbourhood exploration strategies are proposed and compared with extensive experiments based on realistic problems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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