Simulation planning and rostering: a discrete event simulation for the crew assignment process in north american freight railroads
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 introduces a discrete event simulation for crew assignments and crew movements as a result of train traffic, labor rules, government regulations and optional crew schedules. The software is part of a schedule development system, FRCOS (Freight Rail Crew Optimization System), that was co-developed by Canadian National (CN) Rail and Circadian Technologies, Inc. The simulation allows verification of the impact of changes to trainflow, labor rules or government regulations on the overall operational efficiency of how crews are called to work. The system helps to evaluate changes to current crew assignments and can test new crew assignment scenarios such as crew schedules. Potential problems can be detected before the actual implementation, saving unnecessary costs. The software is also used to assess the impact of traffic changes on existing crew schedules in order to implement reactive corrections to these schedules.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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