An Exact Algorithm for the Capacitated Arc Routing Problem with Deadheading Demand
Why this work is in the frame
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Bibliographic record
Abstract
We study an extension of the capacitated arc routing problem (CARP) called the capacitated arc routing problem with deadheading demand (CARPDD). This problem extends the classical capacitated arc routing problem by introducing an additional capacity consumption incurred by a vehicle deadheading an edge. It can be used, e.g., to model time or distance constrained arc routing problems. We show that the strongest CARP lower bounds can be weak when directly applied to the CARPDD, and we introduce a new family of valid inequalities shown to significantly strengthen these bounds. We develop an exact algorithm for the CARPDD based on cut-and-column generation and branch and price, and we report extensive computational results on a large set of benchmark instances. The same exact algorithm is also tested on classical CARP benchmark sets and is shown to improve upon the best known exact algorithms for the CARP.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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