Optimization model of staffing for aircraft ground handling in the case of personnel substitutability
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
The presented article deals with the mathematical modeling of aircraft ground handling on the service apron to utilize ground personnel more efficiently in the case of existing substitutability of workers. This article proposes a supporting decision-making tool for effective planning of the aircraft ground handling. This tool will be used for a selected type of aircraft and using the minimum number of personnel participating in the aircraft ground handling procedure. The optimization is based on the original mathematical programming model and its solution. Computational experiments verifying the functionality of the proposed model were performed on current data from the Ostrava International Regional Airport in the Czech Republic. The originality of the proposed approach (apart from the original model) comes with introducing the substitutability of workers of individual qualifications and the decomposition of workgroups composed of workers of the same qualification down to the level of individual workers. Above-mentioned decomposition of workgroups enables the flexible and separate transfer of individual workers included in the same groups between activities in the event of downtime of the given group and the existence of an activity that is not covered by the required number of workers. The substitutability of workers and the decomposition of individual groups down to the level of individual workers will make it possible to lower the number of workers or verify that the number of workers is optimal and eliminate potential staff downtime.
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 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