An exact method for solving the manufacturing cell formation problem
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
The cell formation problem is extensively studied in the literature, but very few authors have proposed exact methods. In this paper a linear binary programming formulation is introduced to generate a solution for the cell formation problem. To verify the behaviour of the proposed model, a set of 35 benchmark problems is solved using the branch and cut method implemented in the IBM ILOG CPLEX 10.11 Optimiser. Moreover, these results allow us to validate the quality of the solution generated with heuristic methods proposed in the literature. This experimentation indicates that, for the smaller problems, the best-known solutions are the same as those generated with CPLEX 10.11 Optimiser. These results indicate a fair confidence in the optimality of the best-known solutions generated by the heuristic methods. Furthermore, our approach is the first exact method providing results of this quality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 | 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