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Record W2718700547

Airspace block organization with metaheurisitics and partitioning packages

2013· preprint· en· W2718700547 on OpenAlexaboutno aff
Charles‐Edmond Bichot, Nicolas Durand

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicVLSI and FPGA Design Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBlock (permutation group theory)Computer scienceMathematicsCombinatorics
DOInot available

Abstract

fetched live from OpenAlex

Abstract—In this paper, different metaheuris-tics applied on an air traffic control problem. This problem is a graph partitioning problem. It can be solved by classical methods which are spectral and multilevel methods. State-of-the-art public-domain graph partitioning packages, CHACO and METIS are used to resolve it. A comparison between results return by these packages and metaheuristics imple-mentations is made for different objective functions of the literature. Metaheuristics used are simulated annealing, ant colony and a new one called fusion fission developed in the LOG laboratory. Experi-mental results show that metaheuristics find better results than classical packages. I.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.757
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.176
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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