Dispatching Buses in a Depot Using Block Patterns
Bibliographic record
Abstract
In this article we consider the problem of assigning parking slots to buses of different types so that the required buses can be dispatched easily in the morning. More precisely, if a bus of a certain type is needed at a given time, the buses that precede it in the lane must have departed already. Thus care must be taken to ensure that the buses arriving in the evening are parked in an order compatible with the types required for the morning departures. Maneuvers (i.e., rearrangements of buses within lanes) might be necessary to achieve this goal. Because the transit authorities need robust solutions to this problem (known as the dispatching problem in the literature), we formulate a model in which the depot lanes are filled according to specific patterns, called one-block or two-block patterns. We present two versions of this model, study their properties, and show that some real-life instances can be solved within reasonable times by a commercial MIP solver. We also demonstrate that the solutions of the model are very robust, and can thus be used by transit authorities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".