Parameter Settings and Baseline Values for High-Speed Rail Emergency Scheduling

Parameter settings and baseline values support a study on emergency scheduling for high-speed rail logistics disruptions. The data, shared by Shuaixin Guo on figshare, was last updated in April 2026. It underpins a Mixed-Integer Linear Programming model and an Adaptive Large Neighborhood Search algorithm validated on a Zhengzhou-Qingdao Express Rail Line case.

Use Cases

• Benchmarking optimization algorithms based on the described MILP model and ALNS algorithm.
• Simulating emergency truck transshipment scenarios based on the described high-speed rail disruption framework.
• Validating route planning and timeliness constraints based on the described multi-level collaborative decision-making model.

Strengths

• Data is openly shared under a CC-BY-4.0 license, permitting reuse with attribution.
• The underlying model was validated on a real-world case (Zhengzhou-Qingdao Express Rail Line) and multi-scale random instances.
• The associated ALNS algorithm achieved a solution quality with a maximum gap of only 0.037% compared to CPLEX.

Limitations

• The dataset is very small at 5.5 KB, indicating limited scope or a parameters-only file.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare, author Shuaixin Guo.

Collection Method

Likely generated as part of a research study proposing an emergency scheduling optimization framework.

Freshness

Last updated 2026-04-28 17:25:28; freshness should be verified.

Geography

Study includes a case based on the Zhengzhou-Qingdao Express Rail Line.