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Record W1747814569 · doi:10.1109/cdc.1995.478826

Stochastic manufacturing systems under unknown demand and robust control criteria

2002· article· en· W1747814569 on OpenAlexaff
E.K. Boukas, Q. Zhang, Guosheng Yin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMathematical optimizationMinimaxMarkov chainBellman equationLipschitz continuityBounded functionMarkov processProduction controlMarkov decision processState spaceStochastic controlMathematicsComputer scienceControl theory (sociology)Function (biology)Production (economics)Optimal controlControl (management)EconomicsStatistics

Abstract

fetched live from OpenAlex

This paper is concerned with robust production and maintenance planning in stochastic manufacturing systems. The machine capacity is assumed to be a Markov chain with finite state space, whereas the demand rate is treated as a bounded disturbance that can be deterministic or stochastic as long as it is adapted with respect to the Markov chain representing the machine capacity. The control variables are the rate of maintenance and the rate of production, and the cost function has a minimax structure. It is shown that the value function is locally Lipschitz and satisfies a Hamilton-Jacobi-Isaacs equation. A sufficient condition for optimal control is 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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.775
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.213
Teacher spread0.193 · 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.

Study designSimulation or modeling
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

Citations0
Published2002
Admission routes1
Has abstractyes

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