Discretization of Emperor Penguins Colony Algorithms with Application to Modular Product Design
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
Modularity concepts attracted the attention of many researchers as it plays an important role in product design problems. Modularity requires dividing a product into a set of modules that are independent between each other and dependent within. The product is represented using Design Structure Matrix (DSM). DSM works as a system representation tool; it visualizes the interrelationship between product elements. In this research, a comparison is conducted between four optimization algorithms: Emperor Penguins Colony (EPC), First Modified Emperor Penguins Colony (MEPC1), Second Modified Emperor Penguins Colony (MEPC2) and Cuckoo Search (CS) optimization algorithms. These four algorithms aim at finding the optimal number of clusters and the optimal assignment of components to clusters, with the objective of minimizing the total coordination cost. Experimental results show that EPC outperforms the other three algorithms.
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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