Construction heuristics for the single row layout problem with machine-spanning clearances
Why this work is in the frame
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Bibliographic record
Abstract
The single row layout problem (SRLP) consists of finding an efficient arrangement of n machines arranged along one side of the material transportation path including clearances between machines. Undesired interactions between machines necessitate large clearances not only considered between adjacent machines, but also between machines arranged further away from each other. This new type of clearances, termed machine-spanning clearances, is considered in this paper. Based on previous works for the SRLP, a modified mathematical model of this problem is established in order to minimize the weighted sum of distances. To generate an initial solution, three construction heuristics are proposed and their performance is tested on several instances newly generated or taken from literature. Their results show that all of them perform well regarding the solution quality as well as the computational efficiency.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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