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Record W2098362641 · doi:10.1139/l10-071

Simulation-based aggregate planning of batch plant operations

2010· article· en· W2098362641 on OpenAlexaffvenue
Xueying Tian, Yasser Mohamed, Simaan AbouRizk

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicAssembly Line Balancing Optimization
Canadian institutionsNorth American Construction Group (Canada)Canadian Natural Resources
Fundersnot available
KeywordsProduction (economics)Aggregate planningAggregate (composite)Supply chainBatch productionKey (lock)AsphaltProduction planningTask (project management)Service levelService (business)Computer scienceEngineeringCivil engineeringOperations researchOperations managementSystems engineeringBusinessEconomics

Abstract

fetched live from OpenAlex

Production and supply of construction materials plays a significant role in the delivery of constructed facilities, especially for concrete and asphalt batch plants. The construction material (e.g., concrete) supply chain presents unique challenges, but is a key factor in successfully delivering facilities. This paper presents the development and application of a simulation-based aggregate planning approach that facilitates modeling and coordination of a batch plant’s supply chain. The tool is applied to a real case of asphalt production operations, where fluctuating demand affects the service level of the production plant and makes the planning of production and inventory processes a challenging task. The model quantifies the effects of different parameters of the asphalt production plant on its level of service and assists in finding the best configurations for the plant’s production, inventory, and distribution processes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.199
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2010
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicAssembly Line Balancing OptimizationFrench-language works237,207