Integrating tabu search and VLSN search to develop enhanced algorithms:\n A case study using bipartite boolean quadratic programs
Why this work is in the frame
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Bibliographic record
Abstract
The bipartite boolean quadratic programming problem (BBQP) is a\ngeneralization of the well studied boolean quadratic programming problem. The\nmodel has a variety of real life applications; however, empirical studies of\nthe model are not available in the literature, except in a few isolated\ninstances. In this paper, we develop efficient heuristic algorithms based on\ntabu search, very large scale neighborhood (VLSN) search, and a hybrid\nalgorithm that integrates the two. The computational study establishes that\neffective integration of simple tabu search with VLSN search results in\nsuperior outcomes, and suggests the value of such an integration in other\nsettings. Complexity analysis and implementation details are provided along\nwith conclusions drawn from experimental analysis. In addition, we obtain\nsolutions better than the best previously known for almost all medium and large\nsize benchmark instances.\n
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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