Distance Between Nodes for High-Speed Rail Logistics Disruption Modeling

A distance matrix likely for nodes in a high-speed rail logistics network, used to model emergency truck transshipment after disruptions. The dataset was created by Shuaixin Guo and last updated on April 28, 2026. It is a small file of 5.5 KB, stored in XLS format.

Use Cases

• Optimizing emergency truck scheduling for goods transshipment based on node distances.
• Validating Mixed-Integer Linear Programming (MILP) models for logistics disruption response.
• Benchmarking Adaptive Large Neighborhood Search (ALNS) algorithms against CPLEX or Genetic Algorithms.
• Simulating multi-level collaborative decision-making covering vehicle deployment and route planning.

Strengths

• Dataset is small at 5.5 KB, facilitating quick download and inspection.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse and modification.
• Associated with a published study that validated model effectiveness using real and random instances.

Limitations

• Row count and column definitions are unknown, which complicates suitability assessment.
• Description metadata is limited; actual data quality and structure require manual inspection after download.

Provenance

Source

Shuaixin Guo via figshare.

Collection Method

Likely derived or calculated for a study on high-speed rail logistics disruption.

Freshness

Last updated 2026-04-28 17:25:31; freshness should be verified.

Geography

The study mentions the Zhengzhou-Qingdao Express Rail Line, suggesting a focus on Chinese rail networks.