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Record W2149852331 · doi:10.1287/inte.1040.0113

Bombardier Flexjet Significantly Improves Its Fractional Aircraft Ownership Operations

2005· article· en· W2149852331 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

VenueINFORMS Journal on Applied Analytics · 2005
Typearticle
Languageen
FieldEngineering
TopicVehicle Routing Optimization Methods
Canadian institutionsPolytechnique MontréalGroup for Research in Decision AnalysisHEC Montréal
Fundersnot available
KeywordsCrewCharterEngineeringAeronauticsOperations researchService (business)Operations managementBusinessMarketing

Abstract

fetched live from OpenAlex

The fractional aircraft market is the fastest growing segment of the business aircraft industry. A fractional aircraft operation is complex—essentially an unscheduled airline in a constantly changing environment. Bombardier Flexjet implemented a comprehensive three-module optimization system to simultaneously maximize its use of aircraft, crews, and facilities. AD OPT Technologies designed the modules, using the GENCOL optimizer developed at GERAD, which employs a column-generation approach to decompose large-scale mixed-integer nonlinear programming problems. Since inception, the project has generated savings in excess of $54 million with projected additional savings of $27 million annually, primarily by lowering crew levels (20 percent), aircraft inventory (40 percent), and supplemental charter aircraft usage (five percent) while increasing aircraft utilization (10 percent). The quality of customer service has remained consistently high, with significant reduction in supply.

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)0.000
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 score0.878
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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