An Optimization Model for the Simultaneous Operational Flight and Pilot Scheduling Problem
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.
Bibliographic record
Abstract
This paper describes and solves the operational pilot scheduling problem for one day of operations. The problem consists in simultaneously modifying, as necessary, the existing flight departure schedules and planned individual work days (duties) while keeping planned aircraft itineraries unchanged. It requires the covering of all flights from one day of operations with available pilots while minimizing changes in both the flight schedule and the next day's planned duties. The newly constructed personalized duties must not exceed the maximum duty duration. Flight precedence constraints, coming from existing fixed aircraft itineraries, must be respected as well. The problem is mathematically formulated as an integer nonlinear multicommodity network flow model with time windows and additional constraints. To solve the problem, a Dantzig-Wolfe decomposition combined with a branch-and-bound method has been used. The master problem comprises the flight-covering constraints and a new set of flight precedence constraints. Subproblems consisting of time-constrained shortest-path problems with linear time costs are solved by a specialized dynamic-programming algorithm. The proposed optimization approach has been tested on several input data sets. All of them have been successfully solved in very short computational time.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it