Evolution of the China Railway Express Consolidation Network and Optimization of Consolidation Routes
Bibliographic record
Abstract
China Rail Express (CRE) is the international container train line that runs between China and Europe. Since the implementation of China’s Belt and Road initiative, CRE has developed rapidly. As most CRE trains travel directly from source to destination without load consolidation, CRE faces issues such as an insufficient cargo supply, a low load factor, and a low profit margin. To address these problems, we analyzed the selection of potential consolidation centers and the optimization of consolidation routes to these centers from the perspective of complex network evolution. First, we constructed rules for generation and evolution of the complex network. Next, we generated logistics connection topology networks for CRE from 2013 to 2017 using those rules. We then optimized the consolidation routes based on the network structures formed from those rules. Chongqing, Xi’an, Chengdu, Zhengzhou, Shenyang, Lanzhou, Urumqi, and Tianjin were selected as potential consolidation centers. We conclude with a sensitivity analyses and a discussion of management implications for CRE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".