An Iterative Bidding Approach Applied to Cost Reduction in the Context of Aircraft Landing 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 presents an agent-based scheduling approach to solve Aircraft Landing Problem aiming at cost reduction. The focus of the research is a setting where the Air Traffic Control System entity (ATC) needs to build a flight schedule for a runway and the airlines have different costs depending on the landing time window assigned to their flights. The airlines agents' (flights) goal is to minimize the deviation between actual landing time and target landing time. On the other hand, the air traffic entity agent seeks to maximize the utilization of a runway by landing as many flights as possible. An iterative bidding mechanism is developed as the negotiation protocol between flights and ATC. The effectiveness of the proposed approach is evaluated through a computational study. The results show that the proposed decentralized scheduling approach computes high quality schedules compared to the optimal solutions derived from a centralized benchmark model, and also abide by the aviation collaborative decision-making principle.
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 | 0.000 | 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