A Vehicle Routing Problem With Option for Outsourcing and Time-Dependent Travel Time
Why this work is in the frame
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Bibliographic record
Abstract
This paper studies the time-dependent vehicle routing problem with private fleet and common carriers (TDVRPPC), which provides an option to outsource the customer requests and considers real-world time-dependent travel times. The problem is commonly seen in the transportation and logistics industries as it considers the impact of changing traffic conditions on travel times, maximum working hour regulations as well as vehicle capacity constraints. The time-dependent travel time is modeled as a piecewise linear function, based on which a mixed integer programming model is proposed for the TDVRPPC. To solve this NP-hard problem, we customize a hybrid algorithm to harness an adaptive large neighborhood search algorithm for exploration and a tabu search for the exploitation of the search. Through constraint relaxation, dynamic and coordinated adjustment of diversification and intensification strengths of the hybridized procedures, as well as an effective segment-based evaluation method, the proposed algorithm performs well on newly generated test instances for the TDVRPPC and on benchmark instances for the simplified vehicle routing problem with private fleet and common carriers (VRPPC).
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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 | 0.001 | 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