Railway Emergency Resource Scheduling Model Results from VEPSO Algorithm

Results from a case study evaluating an emergency resource scheduling model for railways under multiple uncertainties. The data likely contains performance metrics for optimization algorithms, including convergence iterations, runtime, and success rates. The dataset was created by Jianping Sun and last updated on 2026-05-19.

Use Cases

• Benchmarking the VEPSO algorithm against PSO, NSGA-II, VEGA, and MOEA/D based on convergence efficiency and solution quality metrics.
• Analyzing the relationship between resource allocation and demand satisfaction under different confidence levels for various accident scenarios.
• Conducting sensitivity analysis on scheduling cost and time based on changes to the resource demand scaling factor.

Strengths

• Includes specific performance metrics: average convergence iterations of 385, average runtime of 273 seconds, and a convergence success rate of 93.3%.
• Model results demonstrate a total demand fulfillment credibility of 0.983 and a stable, approximately linear response to demand changes.
• The dataset is small (5.5 KB), facilitating quick download and inspection.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale analysis.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Jianping Sun

Collection Method

Likely generated from computational experiments and case studies of the proposed railway emergency resource scheduling model.

Freshness

Last updated 2026-05-19 17:30:51; freshness should be verified.