MétaCan
Menu
Back to cohort
Record W4240904317 · doi:10.1109/wsc.2004.1371478

Evaluating the Performance of Supply Chain Simulations with Tradeoffs Between Multiple Obljectives

2005· article· en· W4240904317 on OpenAlex
P. Suwanruji, S.T. Enns

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

VenueProceedings of the 2004 Winter Simulation Conference, 2004. · 2005
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSupply chainComputer scienceRange (aeronautics)Industrial engineeringRisk analysis (engineering)Operations researchEngineeringBusiness

Abstract

fetched live from OpenAlex

Simulation is well suited to the development and analysis of supply chain models, since the problems of interest tend to be complex and encompass uncertainty. However, there are typically multiple performance objectives that tend to conflict. A major problem in supply chain studies is that assumptions need to be made about the performance tradeoffs involved. Therefore, the conclusions may not be general. In this paper we develop an approach that allows both delivery performance and inventory levels to be considered over a range of tradeoffs. By developing tradeoff curves and analyzing the area under each we are able to reach conclusions that are more general and can be shown to be statistically valid.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.246
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.142
GPT teacher head0.403
Teacher spread0.261 · 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