A metaheuristic for a time-dependent vehicle routing problem with time windows, two vehicle fleets and synchronization on a road network
Why this work is in the frame
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Bibliographic record
Abstract
In this work, we extend the time-dependent vehicle routing problem with time windows on a road network by considering two types of vehicles, large and small, to serve customers. Motivated from city logistics applications, large vehicles are forbidden from the downtown area. Accordingly, goods must be transferred from large to small vehicles to serve downtown customers. This leads to synchronization issues at transfer points, which are special locations without storage capacity. The problem is not a pure two-echelon vehicle routing problem, since customers outside of the downtown area can be served directly by large vehicles. The problem is further compounded by the presence of time-dependent travel times that are defined on the arcs of the road network and are used to model congestion periods. To solve this difficult problem, we propose an adaptation of the Slack Induction by String Removals metaheuristic, which is state-of-the-art for the classical capacitated vehicle routing problem. Computational results on a set of test instances with different characteristics empirically demonstrate the optimization capabilities of this new metaheuristic on a problem which is much more complicated than the capacitated vehicle routing problem. • A state-of-the-art metaheuristic for the capacitated vehicle routing problem is modified to solve a difficult variant. • The problem considered is motivated by city logistics applications. • The problem involves time dependency and time windows. • The problem also involves two types of vehicles with synchronization at transfer points on a road network. • Computational results are reported using well known benchmark instances for the time-dependent vehicle routing problem with time windows.
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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