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Record W2004985180 · doi:10.1287/inte.30.2.41.11673

Air Transat Uses ALTITUDE to Manage Its Aircraft Routing, Crew Pairing, and Work Assignment

2000· article· en· W2004985180 on OpenAlexaffabout
Jacques Desrosiers, Arielle Lasry, Daniel McInnis, Marius M. Solomon, François Soumis

Bibliographic record

VenueINFORMS Journal on Applied Analytics · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle Routing Optimization Methods
Canadian institutionsPolytechnique MontréalGroup for Research in Decision AnalysisHEC Montréal
Fundersnot available
KeywordsCharterScheduling (production processes)Operations researchCrew schedulingCrewFlexibility (engineering)NavyWork (physics)Computer scienceOperations managementEngineeringAeronautics

Abstract

fetched live from OpenAlex

Air Transat operates charter flights to vacation spots. In 1993, it had an opportunity to expand, but its manual planning and scheduling system could not support rapid growth. Air Transat acquired the airline operations management system ALTITUDE, a three-module optimization package for aircraft routing, crew pairing, and monthly work assignment. The system helped the airline to streamline planning and scheduling and to focus on its core business and expansion rather than internal operational problems. By reducing the planning cycle, increasing operational flexibility, and supporting marketing, the system helped the company to become the largest charter operator in Canada. ALTITUDE ensures cost-effective solutions by optimizing planning and scheduling problems and allowing easy interfacing among them. It saved the company an estimated eight to 12 percent of total costs during the first year and over a million dollars during the second year in operation.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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 designNot applicable
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

Citations25
Published2000
Admission routes2
Has abstractyes

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