The electric vehicle routing problem with shared charging stations
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
Abstract We introduce the electric vehicle routing problem with shared charging stations (E‐VRP‐SCS). The E‐VRP‐SCS extends the electric vehicle routing problem with nonlinear charging function (E‐VRP‐NL) by considering several companies that jointly invest in charging stations (CSs). The objective is to minimize the sum of the fixed opening cost of CSs and the drivers cost. The problem consists of deciding the location and technology of the CSs and building the routes for each company. It is solved by means of a multistart heuristic that performs an adaptive large neighborhood search coupled with the solution of mixed integer linear programs. It also contains a number of advanced efficient procedures tailored to handle specific components of the E‐VRP‐SCS. We perform extensive computational experiments on benchmark instances. We assess the competitiveness of the heuristic on the E‐VRP‐NL and derive 38 new best known solutions. New benchmark results on the E‐VRP‐SCS are presented, solved, and analyzed.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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