Electric-vehicle routing problem with time windows and energy minimization: green logistics with same-day delivery approaches
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
Electric Vehicle (EV)-based last-mile delivery has been studied in recent years due to its theoretical and practical importance. EVs are known for their eco-friendliness and no air pollution in Green Logistics. However, there is no work on integrating the energy consumption and same-day delivery approaches with Electric-Vehicle Routing Problem with Time Windows (EVRP- TW). The influence of payload weights on the EVs energy consumption is considerable and should be considered when planning routes. This work presents the Prize-Collecting EVRP- TW with Energy Minimization (PC-EVRP- TW-EM), finding the optimal routes of EV s to visit the customers with prime membership (same-day service) and consume less battery energy. A mixed-integer program models the PC-EVRP- TW-EM. The results show the efficiency of the proposed approach, reducing the energy consumption and usage cost of EVs by an average of 32.97% and 29.17%, respectively.
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 | 0.000 | 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 | 0.000 | 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