Algorithm Parameters and Simulation Results for Railway Emergency Resource Scheduling

Jianping Sun's dataset from 2026 contains algorithm parameters and simulation results for a railway emergency resource scheduling model. The data, stored in an XLS file of 5.5 KB, supports a study that integrates fuzzy credibility constraints with interval programming to minimize scheduling time and cost. The results compare the performance of the VEPSO algorithm against PSO, NSGA-II, VEGA, and MOEA/D.

Use Cases

• Benchmarking multi-objective optimization algorithms based on the described convergence efficiency and solution quality metrics.
• Analyzing the sensitivity of scheduling cost and time to changes in resource demand based on the described scaling factor analysis.
• Studying the application of fuzzy-random variables and interval programming for modeling uncertainty in logistics.
• Evaluating solution strategies for problems with complex Pareto fronts based on the described constraint-handling method.

Strengths

• Includes specific performance metrics for the VEPSO algorithm, such as an average convergence iteration count of 385 and a runtime of 273 seconds.
• The underlying model's response to demand changes is quantified, showing a 16.0529% cost change and 50% time change for a specific scaling factor.

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.
• The dataset is very small at 5.5 KB, indicating limited scope, likely containing summary results rather than raw simulation logs.

Provenance

Source

Jianping Sun via figshare

Collection Method

Likely generated from computational simulations of an optimization model.

Freshness

Last updated 2026-05-19 17:30:49; freshness should be verified.