A Simulation-Based Dynamic Programming Method for Interchange Scheduling of Port Collecting and Distributing Network
Bibliographic record
Abstract
As one of the effective methods to reduce congestion, grade intersection has already been changed to interchange in port collecting and distributing network (PCDN) of many Chinese ports, since the first interchange was built in the PCDN of Dalian port in 1924. Due to the growing demand for port freight transportation, congestion in PCDN is becoming one of the inevitable problems that need to be solved. This paper addresses the best interchange scheduling multistage decision problem in PCDN at a network level. The main challenges are how to estimate the delay time and cope with high uncertainties in port network and PCDN. Therefore, a simulation-based dynamic programming (DP) model is proposed with the purpose of minimizing total cost in lifetime period by combining a DP model and two nested simulation models together. Two simulation models are built to figure out the delay cost in the optimization model, which cannot be calculated by mathematical analysis due to complex vehicle travel patterns and irregular traffic volume caused by random events, such as the arrival pattern of ships’, natural conditions, and storage period of cargos. Finally, a real project in northern China is presented as a case study. The proposed method can be applied in similar cases and can help solve analogous complicated multistage problems.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".