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Record W2143374468 · doi:10.1504/ijhpcn.2006.013483

Solving the Dynamic Plant Layout Problem using a new hybrid meta-heuristic algorithm

2006· article· en· W2143374468 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of High Performance Computing and Networking · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMathematical optimizationHeuristicComputer scienceQuadratic assignment problemMeta heuristicRemainderQuadratic equationAlgorithmOptimization problemMathematicsArithmetic

Abstract

fetched live from OpenAlex

The Quadratic Assignment Problem (QAP) can be used to formulate the Facility Layout Problem (FLP). The Dynamic Plant Layout Problem (DPLP) extends the FLP. Of the attempted 48 DPLP instances, 29 now have new best-known solution. With respect to the six department instances that all have a known optimal solution, optimal solutions were obtained for two, for which no heuristic had been found before, and previously found optimal solutions were matched for the remainder. With respect to the 15 and 30 department instances, none of which has a known optimal solution, only three current best-known solutions could not be obtained.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.774
Threshold uncertainty score0.434

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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