Deadlock-free scheduling of flexible job shops with limited capacity buffers
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, Mixed Integer Programming (MIP) formulations of the deadlock-free job shop scheduling problem are proposed. The presence of buffer space with limited capacity is considered. This research work also proposes a novel operations insertion algorithm based on the rank matrix (or Latin rectangle). In this algorithm, rank matrices are used to generate the schedules and to check for deadlock situations. Finally, an insertion algorithm is proposed to insert transportation operations in the obtained schedules. Performance evaluations of the proposed mathematical models and the proposed algorithm are conducted. The results show that the mathematical models outperform a model presented earlier in the literature. The results also show that the proposed algorithm obtains the same or better solutions when compared to other solution methodologies reported in the literature. [Submitted 31 July 2007; Revised 14 October 2007; Accepted 14 October 2007]
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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