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Record W2009400799 · doi:10.1504/ejie.2008.017685

Deadlock-free scheduling of flexible job shops with limited capacity buffers

2008· article· en· W2009400799 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

VenueEuropean J of Industrial Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicScheduling and Optimization Algorithms
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMathematical optimizationComputer scienceScheduling (production processes)Integer programmingJob shop schedulingWorkloadDeadlockAlgorithmOperations researchMathematicsDistributed computingSchedule

Abstract

fetched live from OpenAlex

In this paper, Mixed Integer Programming (MIP) formulations of the deadlock-free job shop scheduling problem are proposed. The presence of buffer space with limited capacity is considered. This research work also proposes a novel operations insertion algorithm based on the rank matrix (or Latin rectangle). In this algorithm, rank matrices are used to generate the schedules and to check for deadlock situations. Finally, an insertion algorithm is proposed to insert transportation operations in the obtained schedules. Performance evaluations of the proposed mathematical models and the proposed algorithm are conducted. The results show that the mathematical models outperform a model presented earlier in the literature. The results also show that the proposed algorithm obtains the same or better solutions when compared to other solution methodologies reported in the literature. [Submitted 31 July 2007; Revised 14 October 2007; Accepted 14 October 2007]

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: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.189
Teacher spread0.149 · 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